psrange: Estimates models with increasing number of comparison...

In multilevelPSA: Multilevel Propensity Score Analysis

Description

Estimates models with increasing number of comparison subjects starting from 1:1 to using all available comparison group subjects.

Usage

psrange(df, treatvar, formula, nsteps = 10, nboot = 10, samples,
  type = c("logistic", "ctree"), ...)

Arguments

df	data frame with variables to pass to glm
treatvar	vector representing treatment placement. Should be coded as 0s (for control) and 1s (for treatment).
formula	formula for logistic regression model
nsteps	number of steps to estimate from 1:1 to using all control records.
nboot	number of models to execute for each step.
samples	the sample sizes to draw from control group for each step.
type	either logistic for Logistic regression (using glm function) or ctree for Conditional Inference Trees (using the ctree function).
...	other parameters passed to glm.

Value

a class of psrange that contains a summary data frame, a details data frame, and a list of each individual result from glm.

multilevelPSA documentation built on May 1, 2019, 9:19 p.m.