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The null distribution of likelihood-ratio statistics in the conditional-logistic linkage model
Yeunjoo E Song1, Robert C Elston
1Department of Epidemiology and Biostatistics, Case Western Reserve University Cleveland, OH, USA.
Frontiers in Genetics
|December 7, 2013
Summary
This study provides approximations for the conditional-logistic likelihood-ratio (CL-LR) statistic distributions in complex trait linkage mapping. These findings offer practical guidance for identifying genes associated with diseases using genetic analysis.
Area of Science:
- Genetics
- Biostatistics
- Computational Biology
Background:
- Olson's conditional-logistic model is suitable for complex trait linkage mapping.
- The asymptotic distribution of the conditional-logistic likelihood-ratio (CL-LR) statistic is unknown for certain models, hindering analysis.
Purpose of the Study:
- To derive approximations for the asymptotic null distributions of CL-LR statistics.
- To compare these approximations with empirical null distributions via simulation.
- To provide guidelines for linkage analysis in complex trait genetics.
Main Methods:
- Derivation of approximations for CL-LR statistic asymptotic null distributions.
- Simulation studies using independent affected sib pairs.
- Comparison of approximated and empirical null distributions.
Main Results:
- Approximations to the asymptotic null distributions of CL-LR statistics were derived.
- Empirical null distributions generally matched approximated distributions.
- An exception was noted for the covariate model with a minimum-adjusted binary covariate.
Conclusions:
- The derived approximations offer valuable guidelines for linkage analysis of complex traits.
- This research aids in the identification of genes contributing to disease traits.
- The study validates the utility of conditional-logistic models in genetic research.
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