The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Heterogeneity in survival analysis
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.
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Cites
An introduction to probability theory and its applications
(1958) · Journal of the Franklin Institute · doi:10.1016/0016-0032(58)90688-4 · Cited by 29,269
Extremes and Related Properties of Random Sequences and Processes
Leadbetter, M. R., Lindgren, G., & Rootzén, H. (1983) · Springer Series in Statistics · doi:10.1007/978-1-4612-5449-2 · Cited by 2,873
The impact of heterogeneity in individual frailty on the dynamics of mortality
Vaupel, J. W., Manton, K. G., & Stallard, E. (1979) · Demography · doi:10.2307/2061224 · Cited by 1,932
The relative survival rate: a statistical methodology.
Ederer, F., Axtell, L. M., & CUTLER, S. J. (1961) · PubMed · Cited by 1,169
An Introduction to Probability Theory and Its Applications. Vol. II
B., H. L., & Feller, W. (1968) · Population (French Edition) · doi:10.2307/1527528 · Cited by 1,154
Survival models for heterogeneous populations derived from stable distributions
HOUGAARD, P. (1986) · Biometrika · doi:10.1093/biomet/73.2.387 · Cited by 716
DIETARY FAT AND DIETARY SUGAR IN RELATION TO ISCHÆMIC HEART-DISEASE AND DIABETES
Yudkin, J. (1964) · The Lancet · doi:10.1016/s0140-6736(64)90002-9 · Cited by 669
Multivariate Generalizations of the Proportional Hazards Model
Clayton, D., & Cuzick, J. (1985) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2981943 · Cited by 625
A class of multivanate failure time distributions
HOUGAARD, P. (1986) · Biometrika · doi:10.1093/biomet/73.3.671 · Cited by 581
Cited by
Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence
Singer, J. D., & Willett, J. B. (2003) · doi:10.1093/acprof:oso/9780195152968.001.0001 · Cited by 10,647
Penalized Survival Models and Frailty
Therneau, T. M., Grambsch, P. M., & Pankratz, V. S. (2003) · Journal of Computational and Graphical Statistics · doi:10.1198/1061860031365 · Cited by 481
Frailty Models in Survival Analysis
Wienke, A. (2010) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420073911 · Cited by 454
Randomization, Statistics, and Causal Inference
Greenland, S. (1990) · Epidemiology · doi:10.1097/00001648-199011000-00003 · Cited by 385
Missov, T. I., & Finkelstein, M. (2011) · Theoretical Population Biology · doi:10.1016/j.tpb.2011.05.001 · Cited by 34
Metadata
- Authors
- Aalen, O. O.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 1988-11
- Volume
- 7
- Issue
- 11
- Pages
- 1121-1137
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2059989630
- Cited by
- 366
- References
- 25
- FWCI
- 5.70
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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