Related Experiment Video
Updated: May 4, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Predictors of attrition among rural breast cancer survivors
Karen Meneses1, Andres Azuero, Xiaogang Su
1School of Nursing, University of Alabama, Birmingham, AL.
Abstract:
Attrition can jeopardize both internal and external validity. The goal of this secondary analysis was to examine predictors of attrition using baseline data of 432 participants in the Rural Breast Cancer Survivors study. Attrition predictors were conceptualized based on demographic, social, cancer treatment, physical health, and mental health characteristics. Baseline measures were selected using this conceptualization. Bivariate tests of association, discrete-time Cox regression models and recursive partitioning techniques were used in analysis. Results showed that 100 participants (23%) dropped out by Month 12. Non-linear tree analyses showed that poor mental health and lack of health insurance were significant predictors of attrition. Findings contribute to future research efforts to reduce research attrition among rural underserved populations.
Related Concept Videos
Longitudinal Research
Cancer Survival Analysis
Ending Relationships
Truncation in Survival Analysis
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Assumptions of Survival Analysis

