Statistical inference in mixed models and analysis of twin and family data.

摘要: Analysis of data from twin and family studies provides the foundation for disease inheritance. The development advanced theory computational software general linear models has generated considerable interest using mixed-effect to analyze data, as a computationally more convenient theoretically sound alternative classical structure equation modeling. Despite long history analysis, some fundamental questions remain unanswered. We addressed two important issues. One is determine necessary sufficient conditions identifiability in mixed effects data. other derive asymptotic distribution likelihood ratio test, which novel due fact that standard regularity are not satisfied. considered series specific yet examples we demonstrated how formulate appropriately reflect our key idea use Cholesky decomposition. Finally, applied method provide precise estimate heritability sets than previously reported estimate.