Package index • WeightIt

Estimate weights

weightit(): Estimate Balancing Weights

weightitMSM(): Generate Balancing Weights for Longitudinal Treatments

summary(<weightit>) plot(<summary.weightit>) summary(<weightitMSM>) plot(<summary.weightitMSM>): Print and Summarize Output

Specific estimation methods

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_super: Propensity Score Weighting Using SuperLearner

method_user: User-Defined Functions for Estimating Weights

Fit weighted regression models

glm_weightit() ordinal_weightit() multinom_weightit() coxph_weightit() lm_weightit(): Fitting Weighted Generalized Linear Models

predict(<glm_weightit>) predict(<ordinal_weightit>) predict(<multinom_weightit>): Predictions for glm_weightit objects

anova(<glm_weightit>): Methods for glm_weightit() objects

summary(<glm_weightit>) summary(<multinom_weightit>) summary(<ordinal_weightit>) summary(<coxph_weightit>) print(<glm_weightit>) vcov(<glm_weightit>) update(<glm_weightit>): Methods for glm_weightit() objects

Modify weights

trim(): Trim (Winsorize) Large Weights

calibrate(): Calibrate Propensity Score Weights

sbps(): Subgroup Balancing Propensity Score

Other functions

get_w_from_ps(): Compute weights from propensity scores

ESS(): Compute effective sample size of weighted sample

weightit.fit(): Generate Balancing Weights with Minimal Input Processing

as.weightit() as.weightitMSM(): Create a weightit object manually

make_full_rank(): Make a design matrix full rank

plot(<weightit>): Plot information about the weight estimation process

.weightit_methods: Weighting methods

Datasets

msmdata: Simulated data for a 3 time point sequential study