cowboy_glm: Run glm with Lasso prescreening built into boostrapped...

In ben-arnold/washb: Internal WASH Benefits Function Package

Run glm with Lasso prescreening built into boostrapped confidence intervals

Description

Run glm with Lasso prescreening built into boostrapped confidence intervals

Usage

cowboy_glm(
  data,
  clusterid = "id",
  Ws,
  forcedW = NULL,
  pair = NULL,
  family = "gaussian",
  B = 200,
  confint.level = 0.95,
  n.cores = 1
)

Arguments

Ws	data frame that includes candidate adjustment covariates to screen
family	GLM model family (gaussian, binomial, poisson, or negative binomial). Use "neg.binom" for Negative binomial.
Y	Outcome variable (continuous, such as LAZ, or binary, such as diarrhea)
pval	The p-value threshold: any variables with a p-value from the lielihood ratio test below this threshold will be returned. Defaults to 0.2
print	Logical for whether to print function output, defaults to TRUE.

Value

Function returns the list of variable names with a likelihood ratio test p-value <0.2 (unless a custom p-value is specified).

ben-arnold/washb documentation built on Dec. 11, 2023, 7:06 p.m.