Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies

Walter W Piegorsch, C. R. Weinberg, J. A. Taylor

Research output: Contribution to journalArticle

351 Citations (Scopus)

Abstract

This article describes how genetic components of disease susceptibility can be evaluated in case-control studies, where cases and controls are sampled independently from the population at large. Subjects are assumed unrelated, in contrast to studies of familial aggregation and linkage. The logistic model can be used to test collapsibility over phenotypes or genotypes, and to estimate interactions between environmental and genetic factors. Such interactions provide an example of a context where non-hierarchical models make sense biologically. Also, if the exposure and genetic categories occur independently and the disease is rare, then analyses based only on cases are valid, and offer better precision for estimating gene-environment interactions than those based on the full data.

Original languageEnglish (US)
Pages (from-to)153-162
Number of pages10
JournalStatistics in Medicine
Volume13
Issue number2
StatePublished - 1994
Externally publishedYes

Fingerprint

Gene-Environment Interaction
Inborn Genetic Diseases
Case-control Study
Logistic Model
Disease Susceptibility
Rare Diseases
Susceptibility
Case-Control Studies
Logistic Models
Genotype
Phenotype
Collapsibility
Gene-environment Interaction
Population
Interaction
Linkage
Aggregation
Valid
Estimate
Design

ASJC Scopus subject areas

  • Epidemiology

Cite this

Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies. / Piegorsch, Walter W; Weinberg, C. R.; Taylor, J. A.

In: Statistics in Medicine, Vol. 13, No. 2, 1994, p. 153-162.

Research output: Contribution to journalArticle

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