pchisqC: Compares full v. reduced logistic regression models with...
In RCPA3: Data and Functions for R Companion to Political Analysis 3rd Ed

pchisqC

R Documentation

Compares full v. reduced logistic regression models with Chi-Squared test

Description

Compares full and reduced logistic regression models with Chi-Square Test to assess whether additional variables of full model are statistically significant.

Usage

pchisqC(reduced, full, digits = 3)

Arguments

`reduced`	The reduced logistic regression model as an object. This is model with fewer independent variables.
`full`	The full logistic regression model as an object. This is model with more independent variables.
`digits`	(Optional) The number of digits to display after decimal point, default is 3.

Value

The chi-squared statistic, df, and p-value as a vector of numbers to test null hypothesis that full model no better than reduced model.

Textbook References

Philip H. Pollock and Barry C. Edwards, An R Companion to Political Analysis, 3rd Edition (Thousand Oaks, CA: Sage Publications, Forthcoming 2022), Chapter 14.
Philip H. Pollock and Barry C. Edwards, The Essentials of Political Analysis, 6th Edition (Thousand Oaks, CA: Sage Publications, 2020), Chapter 9. ISBN-13: 978-1506379616; ISBN-10: 150637961.

Examples

   library(RCPA3)
   
   
   model_full <- logregC(battleground2020 ~ vep16.turnout + adv.or.more, data=states)
   model_reduced <- logregC(battleground2020 ~ vep16.turnout, data=states)
   
   pchisqC(reduced=model_reduced, full=model_full)

RCPA3 documentation built on May 29, 2024, 12:19 p.m.