Related Experiment Video
Updated: Jun 28, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Permutation tests for joinpoint regression with applications to cancer rates
1Syracuse University, Department of Mathematics, 215 Carnegie Building, Syracuse University, Syracuse, NY 13244-1150, USA. hjkim@mailbox.syr.edu
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.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Kaplan-Meier Approach
Assumptions of Survival Analysis
Comparing the Survival Analysis of Two or More Groups
The Mantel-Cox Log-Rank Test
Cancer Survival Analysis