ljr11: Test coefficients conditioned on K=1 joinpoint.

In ljr: Logistic Joinpoint Regression

Description

This function performs the likelihood ratio tests to find p-values in testing the significance of each of the coefficients as well as the intercept and ordered observation times. The p-values are determined by a Monte Carlo method.

Usage

ljr11(y,n,tm,X,ofst,R=1000)

Arguments

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.

Details

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

Value

pvals

The estimates of the p-values via simulation.

Author(s)

The authors are Michal Czajkowski, Ryan Gill, and Greg Rempala. The software is maintained by Ryan Gill [e-mail].

References

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

See Also

ljr1

Examples

 data(kcm)
 attach(kcm)
 set.seed(12345)
## Not run: ljr11(Count,Population,Year+.5,R=20) 

Example output

ljr 1.4-0 loaded

ljr documentation built on May 1, 2019, 7:50 p.m.