| glmperm-package {glmperm} | R Documentation |
A permutation Likelihood Ratio test is used for inference in generalized linear models. The procedure is useful when parameter estimates fail to converge or are unreliable due to small sample size.
| Package: | glmperm |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2009-09-07 |
| License: | GPL-3 |
The function prr.test requires that the user identifies one independent variable for which a test of the null hypothesis (that the regression coefficient is zero) is to be performed. This variable of interest is supplied as a character string 'var'; the full model is supplied as a formula.
Douglas M. Potter (original version for logistic regression models), Wiebke Werft (extension for generalized linear models)
Maintainer: Wiebke Werft <w.werft@dkfz.de>
Potter D.M. (2005) A permutation test for inference in logistic regression with small- and moderate-sized datasets. Statistics in Medicine, 24:693-708.
### Example 1 ### nobs<-40 x1<-rnorm(nobs) x2<-rnorm(nobs) xx<-cbind(x1,x2) x0<-rnorm(nobs)+x1+x2 y<-x0+x1+x2+2*rnorm(nobs) y<-ifelse(y>0,1,0) LRtest1 <- prr.test(y~x0+x1+x2,var="x0", family=binomial()) summary(LRtest1) ### Example 2 ### utils::data(anorexia, package="MASS") LRtest <- prr.test(Postwt ~ Prewt + Treat, var="Prewt", data = anorexia, family = gaussian()) summary(LRtest)