Missing data and Bayesian Imputation

[NathanielF]

A notebook on Missing Data methods and Bayesian imputation

Related to https://github.com/pymc-devs/pymc-examples/issues/461

This notebook aims to showcase methods for imputation of missing data using primarily bayesian methods. We will focus on a dataset which records employee satisfaction metrics drawn from the book Applied Missing Data Analysis. We will demonstrate how FIML and Bayesian imputation methods work using the Multivariate normal distribution differ and we also want to show how approximate the multivariate distribution using the sequential chained equation methods.

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[NathanielF]

I think this is ready for review now. It's quite long and covers a number of approaches to imputation.

(I) We discuss the taxonomies of missing-ness (MCAR), (MAR) and (MNAR). I try to set it up as a prelude to considerations about causal inference.

(ii) FIML and MLE approaches to estimating a multivariate model given missing data (iii) Bayesian imputation of missing values using the multivariate gaussian and the posterior predictive distribution (iv) Two examples of imputation using sequential regression equations

Each of the approaches so far is presented in the Enders book and our estimates match those presented there.

(v) I apply the missing data imputation to hierarchical model and estimate the values of the missing data informed by the structure of "team" clusters in our employee data set. The model is estimated using the blackjax sampler and shows divergences, but converges nicely with good Rhat numbers...,. I use the differences in imputation patterns between the hierarchical model and the simpler regression models to argue for why we need to be aware of heterogenous patterns of imputation and how this is analogous to concerns in causal inference of heterogenous treatment effects.

We finish on a wrap up and celebration of the flexibility of bayesian modelling in an enterprise that has work with confounding and complexity.

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fonnesbeck commented on 2023-01-24T02:41:15Z ----------------------------------------------------------------

The table looks janky. Does it need to be placed in a code block to enforce monospace?

NathanielF commented on 2023-01-24T10:55:40Z ----------------------------------------------------------------

Fair. It was a bit needless. I've taken another approach just adding the patterns of missing-ness as a pandas dataframe:

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fonnesbeck commented on 2023-01-24T02:41:16Z ----------------------------------------------------------------

Should add a legend if possible.

NathanielF commented on 2023-01-24T11:02:17Z ----------------------------------------------------------------

Done.

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fonnesbeck commented on 2023-01-24T02:41:17Z ----------------------------------------------------------------

Perhaps add a sentence or two interpreting these plots?

NathanielF commented on 2023-01-24T10:56:09Z ----------------------------------------------------------------

Updated and added some more explanatory text

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fonnesbeck commented on 2023-01-24T02:41:18Z ----------------------------------------------------------------

Line #15.        pm.Potential("x_logp", pm.logp(rv=pm.MvNormal.dist(mus, chol=cov_flat_prior), value=x))

Why are potentials being constructed here rather than just imputing with the MvNormal likelihood? Does that not work anymore? (perhaps I'm missing something obvious)

_NathanielF commented on 2023-01-24T10:57:31Z_ ----------------------------------------------------------------

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

Lower case y in "PyMC"

NathanielF commented on 2023-01-24T10:57:43Z ----------------------------------------------------------------

Adjusted!

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

I'm not sure printing out the entire idata object is helpful, given how large and verbose it is. Maybe pull a few elements that are interesting?

NathanielF commented on 2023-01-24T10:59:00Z ----------------------------------------------------------------

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

fonnesbeck commented 1 year ago

Great tutorial!

NathanielF commented 1 year ago

Fair. It was a bit needless. I've taken another approach just adding the patterns of missing-ness as a pandas dataframe:

---

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NathanielF commented 1 year ago

Updated and added some more explanatory text

---

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NathanielF commented 1 year ago

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

---

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NathanielF commented 1 year ago

Adjusted!

---

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NathanielF commented 1 year ago

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Thank you for taking the time to review!! Glad you liked it.

NathanielF commented 1 year ago

Done.

---

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NathanielF commented 1 year ago

Just giving this a little nudge @drbenvincent. Hope your weekend move went smoothly!?

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drbenvincent commented on 2023-02-01T10:53:36Z ----------------------------------------------------------------

Update to February

NathanielF commented on 2023-02-01T19:17:55Z ----------------------------------------------------------------

Done

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drbenvincent commented on 2023-02-01T10:53:37Z ----------------------------------------------------------------

There's no content in this intro section. Maybe just delete heading?

NathanielF commented on 2023-02-01T19:39:42Z ----------------------------------------------------------------

Done

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drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

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drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

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drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

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drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

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NathanielF commented 1 year ago

Yes

---

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NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

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NathanielF commented 1 year ago

Changed this

---

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NathanielF commented 1 year ago

Linked to that notebook too.

---

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NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

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drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

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drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

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NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

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drbenvincent commented 1 year ago

👍🏻

---

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NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

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fonnesbeck commented on 2023-01-24T02:41:16Z ----------------------------------------------------------------

Should add a legend if possible.

NathanielF commented on 2023-01-24T11:02:17Z ----------------------------------------------------------------

Done.

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:17Z ----------------------------------------------------------------

Perhaps add a sentence or two interpreting these plots?

NathanielF commented on 2023-01-24T10:56:09Z ----------------------------------------------------------------

Updated and added some more explanatory text

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:18Z ----------------------------------------------------------------

Line #15.        pm.Potential("x_logp", pm.logp(rv=pm.MvNormal.dist(mus, chol=cov_flat_prior), value=x))

Why are potentials being constructed here rather than just imputing with the MvNormal likelihood? Does that not work anymore? (perhaps I'm missing something obvious)

_NathanielF commented on 2023-01-24T10:57:31Z_ ----------------------------------------------------------------

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

Lower case y in "PyMC"

NathanielF commented on 2023-01-24T10:57:43Z ----------------------------------------------------------------

Adjusted!

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

I'm not sure printing out the entire idata object is helpful, given how large and verbose it is. Maybe pull a few elements that are interesting?

NathanielF commented on 2023-01-24T10:59:00Z ----------------------------------------------------------------

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

fonnesbeck commented 1 year ago

Great tutorial!

NathanielF commented 1 year ago

Fair. It was a bit needless. I've taken another approach just adding the patterns of missing-ness as a pandas dataframe:

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Updated and added some more explanatory text

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Adjusted!

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Thank you for taking the time to review!! Glad you liked it.

NathanielF commented 1 year ago

Done.

---

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NathanielF commented 1 year ago

Just giving this a little nudge @drbenvincent. Hope your weekend move went smoothly!?

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:36Z ----------------------------------------------------------------

Update to February

NathanielF commented on 2023-02-01T19:17:55Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:37Z ----------------------------------------------------------------

There's no content in this intro section. Maybe just delete heading?

NathanielF commented on 2023-02-01T19:39:42Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

Yes

---

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NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

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NathanielF commented 1 year ago

Linked to that notebook too.

---

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NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

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• Githubissues is a development platform for aggregating issues.

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fonnesbeck commented on 2023-01-24T02:41:17Z ----------------------------------------------------------------

Perhaps add a sentence or two interpreting these plots?

NathanielF commented on 2023-01-24T10:56:09Z ----------------------------------------------------------------

Updated and added some more explanatory text

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:18Z ----------------------------------------------------------------

Line #15.        pm.Potential("x_logp", pm.logp(rv=pm.MvNormal.dist(mus, chol=cov_flat_prior), value=x))

Why are potentials being constructed here rather than just imputing with the MvNormal likelihood? Does that not work anymore? (perhaps I'm missing something obvious)

_NathanielF commented on 2023-01-24T10:57:31Z_ ----------------------------------------------------------------

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

Lower case y in "PyMC"

NathanielF commented on 2023-01-24T10:57:43Z ----------------------------------------------------------------

Adjusted!

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

I'm not sure printing out the entire idata object is helpful, given how large and verbose it is. Maybe pull a few elements that are interesting?

NathanielF commented on 2023-01-24T10:59:00Z ----------------------------------------------------------------

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

fonnesbeck commented 1 year ago

Great tutorial!

NathanielF commented 1 year ago

Fair. It was a bit needless. I've taken another approach just adding the patterns of missing-ness as a pandas dataframe:

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Updated and added some more explanatory text

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Adjusted!

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Thank you for taking the time to review!! Glad you liked it.

NathanielF commented 1 year ago

Done.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just giving this a little nudge @drbenvincent. Hope your weekend move went smoothly!?

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:36Z ----------------------------------------------------------------

Update to February

NathanielF commented on 2023-02-01T19:17:55Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:37Z ----------------------------------------------------------------

There's no content in this intro section. Maybe just delete heading?

NathanielF commented on 2023-02-01T19:39:42Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

Yes

---

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NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

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NathanielF commented 1 year ago

Linked to that notebook too.

---

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NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

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• Githubissues is a development platform for aggregating issues.

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fonnesbeck commented on 2023-01-24T02:41:18Z ----------------------------------------------------------------

Line #15.        pm.Potential("x_logp", pm.logp(rv=pm.MvNormal.dist(mus, chol=cov_flat_prior), value=x))

Why are potentials being constructed here rather than just imputing with the MvNormal likelihood? Does that not work anymore? (perhaps I'm missing something obvious)

_NathanielF commented on 2023-01-24T10:57:31Z_ ----------------------------------------------------------------

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

Lower case y in "PyMC"

NathanielF commented on 2023-01-24T10:57:43Z ----------------------------------------------------------------

Adjusted!

review-notebook-app[bot] commented 1 year ago

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

I'm not sure printing out the entire idata object is helpful, given how large and verbose it is. Maybe pull a few elements that are interesting?

NathanielF commented on 2023-01-24T10:59:00Z ----------------------------------------------------------------

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

fonnesbeck commented 1 year ago

Great tutorial!

NathanielF commented 1 year ago

Fair. It was a bit needless. I've taken another approach just adding the patterns of missing-ness as a pandas dataframe:

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Updated and added some more explanatory text

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Adjusted!

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Thank you for taking the time to review!! Glad you liked it.

NathanielF commented 1 year ago

Done.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just giving this a little nudge @drbenvincent. Hope your weekend move went smoothly!?

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:36Z ----------------------------------------------------------------

Update to February

NathanielF commented on 2023-02-01T19:17:55Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:37Z ----------------------------------------------------------------

There's no content in this intro section. Maybe just delete heading?

NathanielF commented on 2023-02-01T19:39:42Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Linked to that notebook too.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

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drbenvincent commented 1 year ago

👍🏻

---

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NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

Lower case y in "PyMC"

NathanielF commented on 2023-01-24T10:57:43Z ----------------------------------------------------------------

Adjusted!

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

I'm not sure printing out the entire idata object is helpful, given how large and verbose it is. Maybe pull a few elements that are interesting?

NathanielF commented on 2023-01-24T10:59:00Z ----------------------------------------------------------------

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

fonnesbeck commented 1 year ago

Great tutorial!

NathanielF commented 1 year ago

Fair. It was a bit needless. I've taken another approach just adding the patterns of missing-ness as a pandas dataframe:

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Updated and added some more explanatory text

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Adjusted!

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Thank you for taking the time to review!! Glad you liked it.

NathanielF commented 1 year ago

Done.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just giving this a little nudge @drbenvincent. Hope your weekend move went smoothly!?

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:36Z ----------------------------------------------------------------

Update to February

NathanielF commented on 2023-02-01T19:17:55Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:37Z ----------------------------------------------------------------

There's no content in this intro section. Maybe just delete heading?

NathanielF commented on 2023-02-01T19:39:42Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Linked to that notebook too.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

• © Githubissues.
• Githubissues is a development platform for aggregating issues.

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fonnesbeck commented on 2023-01-24T02:41:19Z ----------------------------------------------------------------

I'm not sure printing out the entire idata object is helpful, given how large and verbose it is. Maybe pull a few elements that are interesting?

NathanielF commented on 2023-01-24T10:59:00Z ----------------------------------------------------------------

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

fonnesbeck commented 1 year ago

Great tutorial!

NathanielF commented 1 year ago

Fair. It was a bit needless. I've taken another approach just adding the patterns of missing-ness as a pandas dataframe:

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Updated and added some more explanatory text

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Adjusted!

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Thank you for taking the time to review!! Glad you liked it.

NathanielF commented 1 year ago

Done.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just giving this a little nudge @drbenvincent. Hope your weekend move went smoothly!?

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:36Z ----------------------------------------------------------------

Update to February

NathanielF commented on 2023-02-01T19:17:55Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:37Z ----------------------------------------------------------------

There's no content in this intro section. Maybe just delete heading?

NathanielF commented on 2023-02-01T19:39:42Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Linked to that notebook too.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

• © Githubissues.
• Githubissues is a development platform for aggregating issues.

[fonnesbeck]

Great tutorial!

[NathanielF]

Fair. It was a bit needless. I've taken another approach just adding the patterns of missing-ness as a pandas dataframe:

---

View entire conversation on ReviewNB

[NathanielF]

Updated and added some more explanatory text

---

View entire conversation on ReviewNB

[NathanielF]

Yes, i think it's broken or not implemented in the latest version. I was getting the same error discussed here: https://discourse.pymc.io/t/automatic-imputation-of-multivariate-models/11029

---

View entire conversation on ReviewNB

[NathanielF]

Adjusted!

---

View entire conversation on ReviewNB

[NathanielF]

Removed the idata_uniform entirely as it was a bit overkill. I left the idata_normal. I like having the ability to inspect the model output. Makes reproductions easier to check for consistency.

---

View entire conversation on ReviewNB

[NathanielF]

Thank you for taking the time to review!! Glad you liked it.

[NathanielF]

Done.

---

View entire conversation on ReviewNB

[NathanielF]

Just giving this a little nudge @drbenvincent. Hope your weekend move went smoothly!?

[review-notebook-app[bot]]

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:36Z ----------------------------------------------------------------

Update to February

NathanielF commented on 2023-02-01T19:17:55Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:37Z ----------------------------------------------------------------

There's no content in this intro section. Maybe just delete heading?

NathanielF commented on 2023-02-01T19:39:42Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Linked to that notebook too.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

• © Githubissues.
• Githubissues is a development platform for aggregating issues.

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drbenvincent commented on 2023-02-01T10:53:37Z ----------------------------------------------------------------

There's no content in this intro section. Maybe just delete heading?

NathanielF commented on 2023-02-01T19:39:42Z ----------------------------------------------------------------

Done

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

Yes

---

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NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

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NathanielF commented 1 year ago

Linked to that notebook too.

---

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NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

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drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

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NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

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drbenvincent commented 1 year ago

👍🏻

---

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NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

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• Githubissues is a development platform for aggregating issues.

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drbenvincent commented on 2023-02-01T10:53:38Z ----------------------------------------------------------------

This might be a good opportunity to cross link to the notebook on censoring and truncation as a different kind of missingness https://www.pymc.io/projects/examples/en/latest/generalized_linear_models/GLM-truncated-censored-regression.html

NathanielF commented on 2023-02-01T19:39:24Z ----------------------------------------------------------------

Linked to that notebook too.

drbenvincent commented on 2023-02-03T09:10:17Z ----------------------------------------------------------------

Sorry if I'm missing it, but can't see a reference to the example

NathanielF commented on 2023-02-03T09:19:59Z ----------------------------------------------------------------

Just above introducing the employee data set below the MNAR definition

drbenvincent commented on 2023-02-03T09:23:41Z ----------------------------------------------------------------

👍🏻

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

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drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes

---

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NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

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NathanielF commented 1 year ago

Linked to that notebook too.

---

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NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

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NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

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drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

• © Githubissues.
• Githubissues is a development platform for aggregating issues.

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View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:39Z ----------------------------------------------------------------

Should the Employee Satisfaction Surveys be a L2 header?

NathanielF commented on 2023-02-01T19:30:45Z ----------------------------------------------------------------

Yes

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Linked to that notebook too.

---

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NathanielF commented 1 year ago

Done

---

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NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

• © Githubissues.
• Githubissues is a development platform for aggregating issues.

[review-notebook-app[bot]]

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:40Z ----------------------------------------------------------------

The whole notebook uses this double hash for code comments. Isn't that a bit atypical, compared to a single hash? It's messing with my mind, thinking that it was intended to be a L2 markdown heading. I'd also recommend the standard single # so that it's consistent with the other notebooks

NathanielF commented on 2023-02-01T19:32:06Z ----------------------------------------------------------------

Changed this

drbenvincent commented on 2023-02-03T09:13:35Z ----------------------------------------------------------------

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

NathanielF commented on 2023-02-03T09:26:53Z ----------------------------------------------------------------

Agh... sorry. I think i've got them all now.

review-notebook-app[bot] commented 1 year ago

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Linked to that notebook too.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

• © Githubissues.
• Githubissues is a development platform for aggregating issues.

[review-notebook-app[bot]]

View / edit / reply to this conversation on ReviewNB

drbenvincent commented on 2023-02-01T10:53:41Z ----------------------------------------------------------------

Could be worth having brief text after the figure to highlight the relevant missingness about these distributions. At a glance, it's not obvious what is going on here in terms of missing data vs bad binning of the histograms.

I see another comment about a legend here, but not seeing one. Did it get committed?

NathanielF commented on 2023-02-01T19:31:47Z ----------------------------------------------------------------

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

drbenvincent commented on 2023-02-03T09:14:42Z ----------------------------------------------------------------

Ah yes, Chris meant legend, but I meant figure caption :)

NathanielF commented 1 year ago

Perfect, thanks @drbenvincent. Will adjust this evening.

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Yes

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Changed this

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Linked to that notebook too.

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Done

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

drbenvincent commented 1 year ago

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

drbenvincent commented 1 year ago

👍🏻

---

View entire conversation on ReviewNB

NathanielF commented 1 year ago

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB

• © Githubissues.
• Githubissues is a development platform for aggregating issues.

[NathanielF]

Perfect, thanks @drbenvincent. Will adjust this evening.

[NathanielF]

Done

---

View entire conversation on ReviewNB

[NathanielF]

Yes

---

View entire conversation on ReviewNB

[NathanielF]

I thought he just meant the legend in the picture i.e. the color labels for Empowerment etc... which were missing at the time he commented but are there now for me.

---

View entire conversation on ReviewNB

[NathanielF]

Changed this

---

View entire conversation on ReviewNB

[NathanielF]

Linked to that notebook too.

---

View entire conversation on ReviewNB

[NathanielF]

Done

---

View entire conversation on ReviewNB

[NathanielF]

That should be good to go now @drbenvincent. I've tidied a few things and added some more explanatory text to sign post what i'm doing a bit more. I think i've also addressed all comments above.

[drbenvincent]

Sorry if I'm missing it, but can't see a reference to the example

---

View entire conversation on ReviewNB

[drbenvincent]

Thanks! A quick find shows up some remaining examples which are not actual L2 markdown headings. ## Percentage Missing in this cell. A bunch in cell 31, one in cell 11.

---

View entire conversation on ReviewNB

[drbenvincent]

Ah yes, Chris meant legend, but I meant figure caption :)

---

View entire conversation on ReviewNB

[NathanielF]

Just above introducing the employee data set below the MNAR definition

---

View entire conversation on ReviewNB

[drbenvincent]

👍🏻

---

View entire conversation on ReviewNB

[NathanielF]

Agh... sorry. I think i've got them all now.

---

View entire conversation on ReviewNB