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A new parametric family for modelling cumulative incidence functions: application to breast cancer data
Author(s) -
Jeong JongHyeon
Publication year - 2006
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/j.1467-985x.2006.00409.x
Subject(s) - cumulative incidence , cumulative distribution function , parametric statistics , nonparametric statistics , incidence (geometry) , statistic , statistics , breast cancer , parametric model , test statistic , mathematics , hazard , computer science , statistical hypothesis testing , econometrics , medicine , cancer , probability density function , cohort , geometry , chemistry , organic chemistry
Summary. Competing risks situations can be encountered in many research areas such as medicine, social science and engineering. The main stream of analyses of those competing risks data has been nonparametric or semiparametric in the statistical literature. We propose a new parametric family to parameterize the cumulative incidence function completely. The new distribution is sufficiently flexible to fit various shapes of hazard patterns in survival data and increases the efficiency of the cumulative incidence estimates over the distribution‐free approaches. A simple two‐sample parametric test statistic is also proposed to compare the cumulative incidence functions between two groups at a given time point. The new parametric approach is illustrated by using breast cancer data sets from the National Surgical Adjuvant Breast and Bowel Project.