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PSweight (version 1.1.5)

Propensity Score Weighting for Causal Inference with Observational Studies and Randomized Trials

Description

Supports propensity score weighting analysis of observational studies and randomized trials. Enables the estimation and inference of average causal effects with binary and multiple treatments using overlap weights (ATO), inverse probability of treatment weights (ATE), average treatment effect among the treated weights (ATT), matching weights (ATM) and entropy weights (ATEN), with and without propensity score trimming. These weights are members of the family of balancing weights introduced in Li, Morgan and Zaslavsky (2018) and Li and Li (2019) .

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Install

install.packages('PSweight')

Monthly Downloads

673

Version

1.1.5

License

GPL (>= 2)

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Maintainer

Last Published

October 28th, 2021

Functions in PSweight (1.1.5)

PSmethod

Fitting propensity score models with different methods
coef.PSweight

Point estimates of PSweight
OUTmethod

Fitting potential outcome regression with different methods
PSweight

Estimate average causal effects by propensity score weighting
print.PStrim

Print the results of PStrim
PStrim

Trim the input data and propensity estimate
plot.SumStat

Plot the distribution of propensity scores and balance statistics
SumStat

Calculate summary statistics for propensity score weighting
NCDS

Illustrative dataset for PSweight
summary.PSweight

Summarize a PSweight object
print.PSweight

Print the results of PSweight
print.SumStat

Print the results of SumStat
print.PSweightsum

Print the results of Summary.PSweight
print.SumSumStat

Print the results of Summary.SumStat
psdata

Simulated dataset for PSweight
vcov.PSweight

Variance of PSweight
summary.SumStat

Summarize a SumStat object.