The results of a null simulation study suggest that the test statistic appears to follow a central chi-square distribution with one degree of freedom under the null hypothesis, even in the presence of missing data and genotyping errors. The power comparison based on a 23 factorial design shows that this LRT is more powerful than the original TDT, even when 20% genotypes in trios are missing and 1% genotypes are mistyped. Including the information of unaffected children in the likelihood calculation appears to increase the power to test marker-disease association. Finally, the application of this LRT to an idiopathic scoliosis dataset and a psoriasis dataset successfully identifies the significant associations between the markers and the disease that were previously published.The linear dependence problem was fixed by a singular value decomposition algorithm (Press et al., 2002). ... Quadratic Approximation), another derivative- free method developed by Powell (2000) for general unconstrained optimization, uses multivariate ... the constrained search region, the discrete grid method can be used to identify several starting points around which the optimal point may lie. ... The largest/smallest of all observed maxima/minima is then 38 Grid-UOBYQA algorithm.
|Title||:||A Family-based Likelihood Ratio Test for General Pedigree Structures that Allows for Missing Data and Genotyping Errors|
|Publisher||:||ProQuest - 2007|