Journal of Biometrics & Biostatistics

Daniel Gianola

Publications

• Research Article
  Meta-Analysis of Quantitative Trait Association and Mapping Studies using Parametric and Non-Parametric Models
  Author(s): Xiao-Lin Wu, Daniel Gianola, Zhi-Liang Hu and James M. ReecyXiao-Lin Wu, Daniel Gianola, Zhi-Liang Hu and James M. Reecy
  
  Meta-analysis is an important method for integration of information from multiple studies. In quantitative trait association and mapping experiments, combining results from several studies allows greater statistical power for detection of causal loci and more precise estimation of their effects, and thus can yield stronger conclusions than individual studies. Various meta-analysis methods have been proposed for synthesizing information from multiple candidate gene studies and QTL mapping experiments, but there are several questions and challenges associated with these methods. For example, meta-analytic fixed-effect models assume homogeneity of outcomes from individual studies, which may not always be true. Whereas random-effect models takes into account the heterogeneity among studies they typically assume a normal distribution of study-specific outcomes. However in reality, the obse.. Read More»
  DOI: 10.4172/2155-6180.S1-001

  Abstract PDF