compare_coefs: Compare shared coefficients across models

In paramhetero: Numeric and Visual Comparisons of Heterogeneity in Parametric Models

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.

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.

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.

Examples

 ##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')

paramhetero documentation built on April 26, 2022, 1:06 a.m.