Abstract
Abstract I discuss the impact of individual heterogeneity in survival analysis. It is well known that this phenomenon may distort what is observed. A general class of mixing (or frailty) distributions is applied, extending a model of Hougaard. The extension allows part of the population to be non‐susceptible, and contains the traditional gamma distribution as a special case. I consider the mixing of both a constant and a Weibull individual rate, and also discuss the comparison of rates from two populations. A number of practical examples are mentioned. Finally, I analyse two data sets, the main one containing data from the Norwegian Cancer Registry on the survival of breast cancer patients. The statistical analysis is of necessity speculative, but may still provide some insight.
Keywords
Affiliated Institutions
Related Publications
Investigating population heterogeneity with factor mixture models.
Sources of population heterogeneity may or may not be observed. If the sources of heterogeneity are observed (e.g., gender), the sample can be split into groups and the data ana...
Finite-Mixture Structural Equation Models for Response-Based Segmentation and Unobserved Heterogeneity
Two endemic problems face researchers in the social sciences (e.g., Marketing, Economics, Psychology, and Finance): unobserved heterogeneity and measurement error in data. Struc...
THE USE OF RESTRICTION ENDONUCLEASES TO MEASURE MITOCHONDRIAL DNA SEQUENCE RELATEDNESS IN NATURAL POPULATIONS. I. POPULATION STRUCTURE AND EVOLUTION IN THE GENUS PEROMYSCUS
ABSTRACT In this study we introduce to natural population analysis a molecular technique that involves the use of restriction endonucleases to compare mitochondrial DNA (mtDNA) ...
Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study
Abstract Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, ...
REBUS‐PLS: A response‐based procedure for detecting unit segments in PLS path modelling
Abstract Structural equation models (SEMs) make it possible to estimate the causal relationships, defined according to a theoretical model, linking two or more latent complex co...
Publication Info
- Year
- 1988
- Type
- article
- Volume
- 7
- Issue
- 11
- Pages
- 1121-1137
- Citations
- 369
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1002/sim.4780071105