Permutation tests for joinpoint regression with applications to cancer rates.

Abstract:

:The identification of changes in the recent trend is an important issue in the analysis of cancer mortality and incidence data. We apply a joinpoint regression model to describe such continuous changes and use the grid-search method to fit the regression function with unknown joinpoints assuming constant variance and uncorrelated errors. We find the number of significant joinpoints by performing several permutation tests, each of which has a correct significance level asymptotically. Each p-value is found using Monte Carlo methods, and the overall asymptotic significance level is maintained through a Bonferroni correction. These tests are extended to the situation with non-constant variance to handle rates with Poisson variation and possibly autocorrelated errors. The performance of these tests are studied via simulations and the tests are applied to U.S. prostate cancer incidence and mortality rates.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Kim HJ,Fay MP,Feuer EJ,Midthune DN

doi

10.1002/(sici)1097-0258(20000215)19:3<335::aid-sim

subject

Has Abstract

pub_date

2000-02-15 00:00:00

pages

335-51

issue

3

eissn

0277-6715

issn

1097-0258

pii

10.1002/(SICI)1097-0258(20000215)19:3<335::AID-SIM

journal_volume

19

pub_type

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