Research synthesis for multiway tables of varying shapes and size
- This thesis will present techniques for synthesizing partially classified contingency tables with complex missing data patterns. Data of this form is prevalent in modern genetics, with disparate research groups performing independent association studies. We will propose models for combining the results of such studies in a single meta- analysis. Two main algorithms are developed in this dissertation. The first is a likelihood-based approach, using the EM algorithm and loglinear models. Secondly, we will propose a Bayesian alternative, utilizing the Data Augmentation algorithm and constrained Dirichlet-Multinomial distributions. These general models will then be extended to deal with data-specific problems; such as retrospective sampling, conditional slices and multiple perspective linked tables. Variance estimation techniques, model-selection criteria and tests for homogeneity are also derived. Mendelian diseases are deterministic in nature, with direct genetic inheritance paths established between parent and offspring. However, the vast majority of inherited diseases are in fact non-Mendelian, such as early-onset Alzheimer's, psoriasis, breast cancer and cystic fibrosis. Here both genetic and non-genetic factors affect inheritance patterns, with multiple genes and environmental factors interacting in a complex fashion. We shall propose methods for the amalgamation of existing clinical research for such diseases. Each study incrementally measures a particular factor or group of factors, but is missing data on the combination of all potentially relevant variables, thereby producing underdetermined results. By integrating these studies into a single meta-analysis, disease prediction can be carried out across the full set of risk factors.
|Type of resource
|electronic; electronic resource; remote
|1 online resource.
|2009, c2010; 2009
|Stanford University, Department of Statistics
|Wong, Wing Hung
|Wong, Wing Hung
|Statement of responsibility
|Submitted to the Department of Statistics.
|Thesis (Ph.D.)--Stanford University, 2010.
- © 2010 by Donal McMahon
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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