Summarize a propensity score fit

summary.causalmixgpd_ps_fit() returns posterior summaries for the monitored PS-model parameters.

Usage

# S3 method for class 'causalmixgpd_ps_fit'
summary(object, pars = NULL, probs = c(0.025, 0.5, 0.975), ...)

Arguments

object

A "causalmixgpd_ps_fit" object.

pars

Optional character vector of PS parameters to summarize. If NULL, summarize all monitored parameters.

probs

Numeric vector of posterior quantiles to report.

...

Unused.

Value

An object of class "summary.causalmixgpd_ps_fit" with elements model and table.

Details

The summary is parameter based. For logit and probit models, it summarizes the posterior draws of the coefficients that determine the latent linear predictor, which is then mapped to \(e(x)\) by the chosen link function. For the naive Bayes option, it summarizes the class-conditional parameters used to factorize the treatment-assignment model.

This function does not compute fitted propensity scores for specific covariate rows. It summarizes the posterior distribution of the PS model itself, which is the nuisance model later used by causal prediction and treatment-effect standardization.