-
I try to use this setting with a binary variable "sel_1" (numeric no factor) in R but the code report this error
```
Error in if (!did_multiplegt_dyn_by_check(df, group, by)) { :
missing value …
-
Differential effects of antiretroviral treatment on immunity and gut microbiome composition in people living with HIV in rural versus urban Zimbabwe - Angela Sofia Burkhart Colorado - Microbiome
htt…
-
Hello,
I am trying to fit a causal forest on an outcome that has a highly right-skewed distribution and mass at zero. Then I want to sort the sample by deciles of predicted treatment effects and calc…
-
# - Visual Diagnostic Tool for Causal Inference: Heterogeneous Treatment Effects
A simple diagnostic plot to examine potential treatment heterogeneity – what’s old is new!
[https://livefreeordichoto…
-
triggered by #3622
DiD in the simplest case is just the interaction effect of time and group dummies in OLS
What support to we need? What extensions and related models would be useful?
### asym…
-
This requires to develop the fast-and-robust bootstrap methodology for robust estimators of multilevel models. Such robust estimators are implemented in package [`robustlmm`](https://cran.r-project.or…
-
Hello,
First of all, thank you for a fantastic package. I am trying run the R version of did_multiplegt_dyn with a control variable. My setup has several observations per (g,t), and a non-absorbing…
urfos updated
2 weeks ago
-
As discussed in this week's backlog meeting, [non-text contrast](https://www.w3.org/WAI/WCAG22/Understanding/non-text-contrast.html) could benefit from content explaining the rational around hover sta…
-
I have 10 treatment levels 0,1,2,...,9. I wanted the confidence interval for treatment effects given a X value using the effect_interval function. I ran the code effect_interval(X=X[:1],T0=1,T1=2).
…
-
Hi, I'm new in the field of Causality and I would like to use your package for my current project. This is a really great toolbox for causal inference. But I have several questions when checking case …