HLtest.Rsq: Goodness-of-fit tests for GLMs for binary data

In binomTools: Performing diagnostics on binomial regression models

Description

Goodness-of-fit tests for GLMs for binary data including the Hosmer-Lemeshow decile test and X-squared test with normal approximation.

Usage

## S3 method for class 'Rsq'
HLtest(object, method = c("deciles", "fixed"),
         decile.type = 8, ...)

## S3 method for class 'HLtest.Rsq'
print(x, digits = getOption("digits"), ...)

## S3 method for class 'Rsq'
X2GOFtest(x, ...)

## S3 method for class 'X2GOFtest.Rsq'
print(x, ...)

Arguments

object	An Rsq object
x	An HLtest.Rsq or an X2GOFtest.Rsq object
method	The type of Hosmer-Lemeshow test to be performed. The "deciles" method should be more accurate (Hosmer et al, 1997)
decile.type	The quantile computation method; see quantile for details
digits	the desired number of printed digits
...	currently not used

Details

These tests are known to have very low power. They are only appropriate when the fitted frequencies are very low and when the covariate pattern dictates strictly binary observations.

Value

For HLtest.Rsq an object of class HLtest.Rsq with components

expected	the expected frequencies in the 2 x 10 entries
observed	the observed frequencies in the 2 x 10 entries
resid	Pearson residuals
X2	the Pearson X-squared statistic
p.value	the p-value for the goodness-of-fit test
method	the method used for the test

For X2GOFtest an object of class X2GOFtest with components

p.value	the p-value for the goodness-of-fit test
z.score	the standardized z-score for the goodness-of-fit test
RSS	the residual sums of squares term
X2	the pearson chi-squared statistic

Author(s)

Rune Haubo B Christensen

References

Hosmer, D.W. and Lemeshow, S. (1980). Goodness of fit tests for the multiple logistic regression model. Communications in Statistics - Theory and Methods, A9(10), p. 1043-1069.

Examples

## Lifted from example(predict.glm):
ldose <- rep(0:5, 2)
numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
sex <- factor(rep(c("M", "F"), c(6, 6)))
SF <- cbind(numdead, numalive=20-numdead)
budworm.lg <- glm(SF ~ sex*ldose, family=binomial)
## summary(budworm.lg)

(Rsq.budworm <- Rsq(budworm.lg))

HLtest(Rsq.budworm)
HLtest(Rsq.budworm, method="fixed")
X2GOFtest(Rsq.budworm)

binomTools documentation built on May 29, 2017, 10:12 p.m.