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家族聚集性研究的功效计算。

Power calculations for familial aggregation studies.

作者信息

Rabbee Nusrat, Betensky Rebecca A

机构信息

Department of Statistics, University of California, Berkeley, California, USA.

出版信息

Genet Epidemiol. 2004 May;26(4):316-27. doi: 10.1002/gepi.10312.

Abstract

Family studies are frequently undertaken as the first step in the search for genetic determinants of disease. Significant familial aggregation of disease is suggestive of a genetic etiology for the disease, and may lead to more focused genetic analyses. Many methods have been proposed in the literature for the analysis of family studies. One model that is appealing for its simplicity of computation and the conditional interpretation of its parameters is the quadratic exponential model (e.g., Zhao and Prentice [1990] Biometrika 77:642-648; Betensky and Whittemore [1996] Appl. Stat. 45:422-429; Hudson et al. [2001a] Am. J. Epidemiol. 153:500-514). However, a limiting factor in its application, as well as that of the other proposed methods, is that power and sample size calculations have not been derived. These calculations are essential for investigators who are designing family studies. Here we derive analytic approximations for power for testing for familial aggregation, for both randomly sampled and nonrandomly sampled families. We also present simulation studies of power for both single- and two-disease cases, both under random and nonrandom sampling.

摘要

家族研究常常作为寻找疾病遗传决定因素的第一步。疾病显著的家族聚集性提示该疾病存在遗传病因,并且可能会促使进行更具针对性的基因分析。文献中已经提出了许多用于分析家族研究的方法。二次指数模型因其计算简单以及参数的条件解释而颇具吸引力(例如,Zhao和Prentice [1990]《生物统计学》77:642 - 648;Betensky和Whittemore [1996]《应用统计学》45:422 - 429;Hudson等人 [2001a]《美国流行病学杂志》153:500 - 514)。然而,其应用以及其他所提出方法的一个限制因素是尚未得出检验效能和样本量的计算方法。这些计算对于设计家族研究的研究者来说至关重要。在此,我们推导了针对家族聚集性检验效能的解析近似值,适用于随机抽样和非随机抽样的家族。我们还展示了在随机抽样和非随机抽样情况下,单病和双病病例检验效能的模拟研究。

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