Learn R Programming

switchSelection (version 1.1.2)

lrtest: Likelihood ratio test

Description

This function performs chi-squared test for nested models.

Usage

lrtest(model1, model2)

Value

The function returns an object of class 'lrtest' that is a list with the following elements:

  • n1 - the number of observations in the first model.

  • n2 - the number of observations in the second model.

  • ll1 - log-likelihood value of the first model.

  • ll2 - log-likelihood value of the second model.

  • df1 - the number of parameters in the first model.

  • df2 - the number of parameters in the second model.

  • restrictions - the number of restrictions in the nested model.

  • value - chi-squared test statistic value.

  • p_value - p-value of the chi-squared test.

Arguments

model1

the first model.

model2

the second model.

Details

Arguments model1 and model2 should be objects of class that has implementations of logLik and nobs methods. It is assumed that either model1 is nested into model2 or vice versa. More precisely it is assumed that the model with smaller log-likelihood value is nested into the model with greater log-likelihood value.

Examples

Run this code
set.seed(123)
# Generate data according to linear regression
n <- 100
eps <- rnorm(n)
x1 <- runif(n)
x2 <- runif(n)
y <- x1 + 0.2 * x2 + eps
# Estimate full model
model1 <- lm(y ~ x1 + x2)
# Estimate restricted (nested) model
model2 <- lm(y ~ x1)
# Likelihood ratio test results
lrtest(model1, model2)

Run the code above in your browser using DataLab