ClassLog: Classification for Logistic Regression

In QuantPsyc: Quantitative Psychology Tools

Classification for Logistic Regression

Description

Provides a Classification analysis for a logistic regression model. Also provides McFadden's Rsq.

Usage

ClassLog(MOD, resp, cut=.5)

Arguments

MOD	Model of class glm where family is bonomial
resp	response variable from data
cut	Arbitrary cut for the proportion deemed '1' in model

Value

A list containing: /CR

• rawtab two-way table of classifications as frequencies

• classtab two-way table of classifications as percentages

• overall Overall percent classifications that are correct

• mcFadden McFaddens pseudoRsq; 1 - ModelDeviance / NullDeviance

Warning

This is a primative function. I have a long to do list. For example, it is not yet written to handle missing observations.

Author(s)

Thomas D. Fletcher [e-mail]

See Also

glm

Examples

# create some data
x <- rnorm(100)
y <- as.numeric(cut(.5*x + rnorm(100), breaks=2))-1
tdf <- data.frame(x=x, y=y)

# run a logistic regression	
glm1 <- glm(y ~ x, data=tdf, family=binomial)

# Get typical summary of results
summary(glm1)

# Classification Analysis
ClassLog(glm1, tdf$y)

QuantPsyc documentation built on June 4, 2022, 1:06 a.m.