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# Power Analysis by Data Simulation in R - Part IV | Julian Quandt
This final part extends the previous part by generalizing data simulation linear mixed-effects models.
[https://julianquandt.com/po…
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Fitting mixed effects models is slow, so it's worth investigating whether we can reuse the output of `lFormula` when the predictors are constant across time. We are also guaranteed that they stay cons…
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The glmmTMB package (https://github.com/glmmTMB/glmmTMB) is a relatively recent addition to R's mixed effects models landscape that combines much of the functionality of both nlme and lme4. I was wond…
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See [specr](https://masurp.github.io/specr/articles/getting-started.html#decomposing-the-variance-in-the-specification-curve) for some inspiration.
- bar chart of the variance in coefficient explai…
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Package [mlmtools](https://cran.r-project.org/package=mlmtools) definitely seems relevant, although it provides a bit of a mix of different things (e.g., some pre-processing stuff, $R^2$, some visuali…
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As I was going thru the documentation of MixedLM, I noticed the predict method only returns the fixed effects mean structure of the model. I was curious as to why this is the case. Shouldn't it return…
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I have written some functions to draw regression plots from mixed models fitted in pure Stan. I wonder whether creating a branch in arviz for such plots would be interesting (guess so by seeing reques…
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It would be very useful if glmmTMB supported different types of ordinal regression, e.g. the proportional odds model (cumulative link logit model).
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As a follow-up of #877
Following families need validation or don't yet work:
- [ ] betabinomial
- [ ] hurdle models
- [ ] zero-inflated models
- [ ] glmmTMB::compois
- [ ] glmmTMB::genpois
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I've started working on homework 6 and am a bit confused about how to compare the mixed models to each other as well as a mixed model to a fixed effects model. For example, I am fairly certain that I'…