A test for detecting etiologic heterogeneity in epidemiological studies

Date

2016-02-17

Author

Karagulle, S.
Kalaylıoğlu Akyıldız, Zeynep Işıl

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Current statistical methods for analyzing epidemiological data with disease subtype information allow us to acquire knowledge not only for risk factor-disease subtype association but also, on a more profound account, heterogeneity in these associations by multiple disease characteristics (so-called etiologic heterogeneity of the disease). Current interest, particularly in cancer epidemiology, lies in obtaining a valid p-value for testing the hypothesis whether a particular cancer is etiologically heterogeneous. We consider the two-stage logistic regression model along with pseudo-conditional likelihood estimation method and design a testing strategy based on Rao's score test. An extensive Monte Carlo simulation study is carried out, false discovery rate and statistical power of the suggested test are investigated. Simulation results indicate that applying the proposed testing strategy, even a small degree of true etiologic heterogeneity can be recovered with a large statistical power from the sampled data. The strategy is then applied on a breast cancer data set to illustrate its use in practice where there are multiple risk factors and multiple disease characteristics of simultaneous concern.

Subject Keywords

Cancer, Disease subtype, Odds ratio, Polychotomous logistic regression, Risk factor, Score test

URI

https://hdl.handle.net/11511/40694

Journal

JOURNAL OF APPLIED STATISTICS

DOI

https://doi.org/10.1080/02664763.2015.1070808

Collections

Department of Statistics, Article

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Citation Formats

S. Karagulle and Z. I. Kalaylıoğlu Akyıldız, “A test for detecting etiologic heterogeneity in epidemiological studies,” JOURNAL OF APPLIED STATISTICS, pp. 538–549, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40694.