ljrkk {ljr}

Test coefficients conditioned on K=k joinpoint.

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

ljrkk(k,y,n,tm,X,ofst,R=1000)

Arguments

k

the pre-specified number of joinpoints (with unknown locations).

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

ljrk

Examples

 data(kcm)
 attach(kcm) 
 set.seed(12345)
## Not run: ljrkk(1,Count,Population,Year+.5,R=20)