Compute coefficient p-values for STAR linear regression using likelihood ratio test

For a linear regression model within the STAR framework, compute p-values for regression coefficients using a likelihood ratio test. It also computes a p-value for excluding all predictors, akin to a (partial) F test.

Usage

pvals(object)

Arguments

object

Object of class "lmstar" as output by lm_star

Value

a list of p+1 p-values, one for each predictor as well as the joint p-value excluding all predictors

Examples

# Simulate data with count-valued response y:
sim_dat = simulate_nb_lm(n = 100, p = 2)
y = sim_dat$y; X = sim_dat$X[,-1] # remove intercept

# Select a transformation:
transformation = 'np'

#Estimate model
fit = lm_star(y~X, transformation = transformation)

#Compute p-values
pvals(fit)
#>        (Intercept)                  X Any linear effects 
#>       3.199957e-01       1.739922e-07       1.739922e-07