Package index • propensity

All functions

ipw() as.data.frame(<ipw>): Inverse Probability Weighted Estimation
is_ps_calibrated(): Check if propensity scores are calibrated
is_ps_trimmed(): Test whether propensity scores have been trimmed
is_ps_truncated(): Test whether propensity scores have been truncated
is_refit(): Check if propensity scores have been refit
is_unit_trimmed(): Identify which units were trimmed
is_unit_truncated(): Identify which units were truncated
propensity propensity-package: propensity: A Toolkit for Calculating and Working with Propensity Scores
ps_calibrate(): Calibrate propensity scores
ps_refit(): Refit a Propensity Score Model on Retained Observations
ps_trim(): Trim Propensity Scores
ps_trim_meta(): Extract trimming metadata from a ps_trim object
ps_trunc(): Truncate (Winsorize) Propensity Scores
ps_trunc_meta(): Extract truncation metadata from a ps_trunc object
new_psw() psw() is_psw() is_stabilized() is_causal_wt() as_psw() estimand() `estimand<-`(): Propensity Score Weight Vectors
wt_ate() wt_att() wt_atu() wt_atm() wt_ato() wt_entropy() wt_atc() wt_cens(): Calculate propensity score weights