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~~- [ ] address #36 by adding option/argument `backend`, giving the option to use either the `tmle` package (current implementation) or `drtmle`~~
- [x] re-think and implement color scheme for plots,…
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Hi，I am confusing about how to use the time and history data. It seems that we should make a model with data of questionnaires k-1 and k-2, but I couldn't find such code implementation. I found you u…
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For your JOSS Review:
Link to your Bioconductor vignette website at the top of the Github repo -- make it really easy to find.
In vignette section 0.2, I run the code and look at `adaptest_out`.…
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The machinery built into `tmle3` for the delta method should be useful in fleshing out `tmle3_Spec_vimshift_delta` to fit a joint TMLE over the shifted counterfactual means and then compute the MSM pa…
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Currently, use the Monte Carlo estimation procedure for the g-formula. An alternative is to use sequential regression. Sequential regression has the advantage of needing fewer models to be specified. …
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At the request from `ethommes` in ticket 141731
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This course is particular useful for me to understand the TMLE procedure. I wonder if the material after lab 10 are public available?
Thank you.
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Hi. While using your package, I got an error message below:
> train Q_lib g_lib vim
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For a particular application I've run into, it would be very useful to be able to incorporate a `weights` argument into `fit_density`, similar in style to what's currently present in standard methods …
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For some reason, the following simple example (with a matrix `W`, instead of a vector) does not work:
```r
library(data.table)
library(tidyverse)
library(condensier)
library(txshift)
set.seed(42…