ljrjk {ljr}R Documentation

Perform test of j vs k joinpoints.

Description

This function tests the null hypothesis of j joinpoint(s) versus the alternative of k joinpoint(s) based on the likelihood ratio test statistic. The p-value is determined by a Monte Carlo method.

Usage

ljrjk(j,k,y,n,tm,X,ofst,R=1000,alpha=.05)

Arguments

j,k pre-specified number of joinpoints in the null and alternative hpyotheses (the smaller is used for the null).
y the vector of Binomial responses.
n the vector of sizes for the Binomial random variables.
tm the vector of ordered observation times.
X a design matrix containing other covariates.
ofst a vector of known offsets for the logit of the response.
R number of Monte Carlo simulations.
alpha significance level of the test.

Details

The re-weighted log-likelihood is the log-likelihood divided by the largest component of n.

Value

pval The estimate of the p-value via simulation.
Coef A table of coefficient estimates.
Joinpoint The estimates of the joinpoint, if it is significant.
wlik The maximum value of the re-weighted log-likelihood.

Author(s)

The authors are Michal Czajkowski, Ryan Gill, and Greg Rempala. The software is maintained by Ryan Gill rsgill01@louisville.edu.

References

Czajkowski, M., Gill, R. and Rempala, G. (2008). Model selection in logistic joinpoint regression with applications to analyzing cohort mortality patterns. {emph Statistics in Medicine} 27, 1508-1526.

See Also

ljrk

Examples

 data(kcm)
 attach(kcm)
 set.seed(12345)
 ljrjk(0,1,Count,Population,Year+.5,R=20)

[Package ljr version 1.2-0 Index]