Cochran-armitage test versus logistic regression in the analysis of genetic association studies
<i>Objective:</i> The Cochran-Armitage trend test based on the linear regression model has become a standard procedure for association testing in case-control studies. In contrast, the logistic regression model is generally used for estimating effect sizes. The aim of this paper is to pr...
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| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2012
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| In: |
Human heredity
Year: 2012, Jahrgang: 73, Heft: 1, Pages: 14-17 |
| ISSN: | 1423-0062 |
| DOI: | 10.1159/000334085 |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1159/000334085 Verlag, Volltext: https://www.karger.com/Article/FullText/334085 
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| Verfasserangaben: | Stefan Wellek, Andreas Ziegler |
| Zusammenfassung: | <i>Objective:</i> The Cochran-Armitage trend test based on the linear regression model has become a standard procedure for association testing in case-control studies. In contrast, the logistic regression model is generally used for estimating effect sizes. The aim of this paper is to propose an approach that allows for association testing and parameter estimation by means of the same statistic. <i>Methods/Results:</i> The trend test is recommendable as a test of no association between genotype and risk of disease. It is a two-sample test for differences between cases and controls with respect to the average number of risk alleles occurring in the genotype of an individual. We argue that this difference is not of primary interest in genetic association studies. It should be replaced with the disease odds ratio, which can be assessed under both cohort sampling and case-control sampling. <i>Conclusion:</i> The Cochran-Armitage trend test should be replaced by the Wald statistic from a logistic regression model for hypothesis testing and estimation in genetic association studies. |
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| Beschreibung: | Gesehen am 14.05.2019 Published online: December 30, 2011 |
| Beschreibung: | Online Resource |
| ISSN: | 1423-0062 |
| DOI: | 10.1159/000334085 |