Weighting for Covariate Balance in Observational Studies

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Documentation for package ‘WeightIt’ version 1.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

as.weightit	Create a 'weightit' object manually
as.weightit.default	Create a 'weightit' object manually
as.weightit.weightit.fit	Create a 'weightit' object manually
as.weightitMSM	Create a 'weightit' object manually
as.weightitMSM.default	Create a 'weightit' object manually
calibrate	Calibrate Propensity Score Weights
calibrate.default	Calibrate Propensity Score Weights
calibrate.weightit	Calibrate Propensity Score Weights
ESS	Compute effective sample size of weighted sample
get_w_from_ps	Compute weights from propensity scores
glm_weightit	Fitting Weighted Generalized Linear Models
lm_weightit	Fitting Weighted Generalized Linear Models
make_full_rank	Make a design matrix full rank
method_bart	Propensity Score Weighting Using BART
method_cbps	Covariate Balancing Propensity Score Weighting
method_ebal	Entropy Balancing
method_energy	Energy Balancing
method_gbm	Propensity Score Weighting Using Generalized Boosted Models
method_glm	Propensity Score Weighting Using Generalized Linear Models
method_ipt	Inverse Probability Tilting
method_npcbps	Nonparametric Covariate Balancing Propensity Score Weighting
method_optweight	Optimization-Based Weighting
method_sbw	Optimization-Based Weighting
method_super	Propensity Score Weighting Using SuperLearner
method_user	User-Defined Functions for Estimating Weights
msmdata	Simulated data for a 3 time point sequential study
plot.summary.weightit	Print and Summarize Output
plot.summary.weightitMSM	Print and Summarize Output
sbps	Subgroup Balancing Propensity Score
summary.glm_weightit	Fitting Weighted Generalized Linear Models
summary.weightit	Print and Summarize Output
summary.weightitMSM	Print and Summarize Output
trim	Trim (Winsorize) Large Weights
trim.default	Trim (Winsorize) Large Weights
trim.weightit	Trim (Winsorize) Large Weights
weightit	Estimate Balancing Weights
weightit.fit	Generate Balancing Weights with Minimal Input Processing
weightitMSM	Generate Balancing Weights for Longitudinal Treatments