paramhetero (version 1.0.0)

compare_coefs: Compare shared coefficients across models

Description

Compares predictor coefficients across models.

Usage

compare_coefs(model_list, padj = "none")

Arguments

model_list

A list of regression models.

padj

A method from p.adjust.methods for adjusting coefficient p-values for multiple testing.

Value

Data frame of shared coefficients, the difference between them, the standard error of the difference, the test statistic comparing them, and the p-value adjusted using the method provided in padj.

Details

This function currently supports comparing coefficients from two models. For each model predictor, coefficients are compared across models. P-values come from a two-sided alternative hypothesis. They can, and should, be adjusted for multiple testing to reduce the probability of chance significant findings.

Examples

# NOT RUN {
 ##Simulate data

 N = 500

 m = rep(1:2, each=N)

 x1 = rnorm(n=N*2)
 x2 = rnorm(n=N*2)
 x3 = rnorm(n=N*2)

 y = x1 + x2 + x3 + rnorm(n=N*2)

 dat = data.frame(m, x1, x2, x3, y)

 m1 = lm(y ~ x1 + x2 + x3, data=dat, subset=m==1)
 m2 = lm(y ~ x1 + x2 + x3, data=dat, subset=m==2)

 mList = list(m1, m2)

 compare_coefs(model_list = mList, padj='fdr')

# }