ncn-foreigners/nonprobsvy

Select, weight and analyze complex sample data — superseded by https://github.com/samplics-org/svy

estimatr: Fast Estimators for Design-Based Inference

The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to some target population of interest.

WeightIt: an R package for propensity score weighting

Honest inference in regression discontinuity designs

Tools for post-processing class probability estimates

R package to compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and ML models. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference

Cluster-robust (sandwich) variance estimators with small-sample corrections