recurrent_propensity: Propensity Score Weighting

In card: Cardiovascular and Autonomic Research Design

Description

recurrent_propensity Adds propensity score to any data set that is being regressed upon.

Usage

recurrent_propensity(data, vars)

Arguments

data	Data frame that contains all covariates and outcomes. First column should be ID
vars	Variables used for regression. Outcome variable must be first.

Details

Using a logistic regression, will take covariates and create propensity scores, and adds the weights. Uses the standard logistic regression to evaluate the propensity score.

Value

Returns a modified table from what was originally given with the new columns propensity scores. Essentially original df + 2 columns.

card documentation built on Sept. 3, 2020, 9:07 a.m.