logiGOF: Goodness of fit tests for a logistic regression model

In logisticDx: Diagnostic tests for logistic regression models

Description

Gives 15 commonly employed measures of goodness of fit for a logistic regression model

Usage

  logiGOF(x, g = 10)

Arguments

x	A model of class glm
g	No. groups (quantiles) into which to split observations for Hosmer-Lemeshow and modified Hosmer-Lemeshow tests.

Value

A list of class logiGOF with the following items:

chiPearCov	Pearsons chi-square, calculated by covariate group, with p value and interpretation
chiPearIndiv	Pearsons chi-square, calculated by individual observation, with p value and interpretation
chiPearTab	Pearsons chi-square, calculated by table of covariate patterns by outcome, with p value and interpretation
OsRo	Osius & Rojek test of the logistic link, with p value and interpretation
chiDevCov	Deviance chi-square, calculated by covariate group, with p value and interpretation
chiDevIndiv	Deviance chi-square, calculated by individual observation, with p value and interpretation
chiDevTab	Deviance chi-square, calculated by table of covariate patterns by outcome, with p value and interpretation
covPatTab	Matrix of covariance patterns, used to calculate above chi-square tests of Pearson residuals and deviance
HosLem	Hosmer & Lemeshow goodness of fit test, with g quantile groups,with p value and interpretation
modHosLem	modified Hosmer & Lemeshow goodness of fit test, with g quantile groups, with p value and interpretation
CesHou	le Cessie, van Houwelingen, Copas & Hosmer unweighted sum of squares test for global goodness of fit, with p value and interpretation
Stuk	Stukels test of the appropriateness of the logistic link, with p value and interpretation
PR2	Pearsons R^2, correlation of observed outcome with predicted
ssR2	Linear regression-like sum-of-squares R^2, using covariate patterns
llR2	Log-likelohood based R^2, calculated by covariate group
ROC	Area under the Receiver Operating Curve, with 95% CI by method of DeLong

Note

A summary method is available

Warning: Will fail if cannot generate a hat matrix for the model using logiDx

Author(s)

Modified Hosmer & Lemeshow goodness of fit test: adapted from existing work by Yongmei Ni

See Also

logiDx

Examples

set.seed(1)
m1 <- genLogiDf(n=100)$model
logiGOF(m1)

logisticDx documentation built on May 2, 2019, 6:30 p.m.