{"product_id":"heterogeneity-in-statistical-genetics-how-to-assess-address","title":"Heterogeneity in Statistical Genetics: How to Assess, Address","description":"\u003cp\u003eIn this review of Heterogeneity in Statistical Genetics: How to Assess, Address, and Account for Mixtures in Association Studies, the bottom line is clear: this book is for researchers and graduate students who need practical statistical tools to model mixtures in genetic association data. The authors present methods that explicitly include \u003cstrong\u003eheterogeneity parameters\u003c\/strong\u003e in test statistics and in power and sample size calculations, making the volume uniquely focused on the pervasive problem of mixtures in genetic studies. It is a technical, method-driven review resource rather than a textbook for beginners.\u003c\/p\u003e\n\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cul\u003e\n \u003cli\u003e\n\u003cstrong\u003eExplicit mixture modeling:\u003c\/strong\u003e The book documents methods that incorporate heterogeneity directly into the design and analysis of genetic and genomic association data, which helps avoid biases from ignoring population mixtures.\u003c\/li\u003e\n \u003cli\u003e\n\u003cstrong\u003eTest statistics with mixture parameters:\u003c\/strong\u003e Developed statistics include mixture parameters as part of the test, improving the relevance of association tests when populations are not homogeneous.\u003c\/li\u003e\n \u003cli\u003e\n\u003cstrong\u003ePower and sample size guidance:\u003c\/strong\u003e The work emphasizes including at least one heterogeneity parameter when performing power and sample size calculations for genetic association studies, offering practical planning tools.\u003c\/li\u003e\n \u003cli\u003e\n\u003cstrong\u003eFocus on association studies:\u003c\/strong\u003e Methods are tailored to map genes for diseases and traits, making the material applicable to case-control and other association study designs.\u003c\/li\u003e\n \u003cli\u003e\n\u003cstrong\u003eTechnical depth:\u003c\/strong\u003e The presentation is methodical and suitable for readers comfortable with statistical theory and genetic study design who want rigorous approaches to mixtures.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eWho It's For\u003c\/h2\u003e\n\u003cp\u003eThis book is aimed at statistical geneticists, biostatisticians, and advanced graduate students engaged in designing or analyzing genetic association studies who need to \u003cstrong\u003eaccount for heterogeneity\u003c\/strong\u003e in their data. It is particularly relevant for those working on complex trait mapping where mixtures of affected and unaffected individuals are present.\u003c\/p\u003e\n\u003cp\u003eResearchers seeking an introductory primer on genetics or casual readers without a quantitative background should look elsewhere, as the book assumes familiarity with statistical testing and study design rather than offering basic genetics instruction.\u003c\/p\u003e\n\n\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n \u003cli\u003eProvides explicit methods to model population mixtures, reducing bias in association analyses.\u003c\/li\u003e\n \u003cli\u003eIntegrates heterogeneity directly into test statistics, enhancing interpretability of results under mixtures.\u003c\/li\u003e\n \u003cli\u003eEmphasizes power and sample size calculations that include heterogeneity parameters, useful for study planning.\u003c\/li\u003e\n \u003cli\u003eWell suited to researchers who need rigorous, method-driven guidance for genetic association work.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n \u003cli\u003eTechnical level is high, so it may be challenging for readers without a strong statistical background.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eSpecifications\u003c\/h2\u003e\n\u003ctable\u003e\n \u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eHeterogeneity in Statistical Genetics: How to Assess, Address, and Account for Mixtures in Association Studies\u003c\/td\u003e\n\u003c\/tr\u003e\n \u003ctr\u003e\n\u003ctd\u003eSeries\u003c\/td\u003e\n\u003ctd\u003eStatistics for Biology and Health\u003c\/td\u003e\n\u003c\/tr\u003e\n \u003ctr\u003e\n\u003ctd\u003eAuthors\u003c\/td\u003e\n\u003ctd\u003eDerek Gordon, Stephen J. Finch, Wonkuk Kim\u003c\/td\u003e\n\u003c\/tr\u003e\n \u003ctr\u003e\n\u003ctd\u003eSubject\u003c\/td\u003e\n\u003ctd\u003eStatistical genetics and biostatistics methods\u003c\/td\u003e\n\u003c\/tr\u003e\n \u003ctr\u003e\n\u003ctd\u003eFocus\u003c\/td\u003e\n\u003ctd\u003eModeling mixtures and heterogeneity in association studies\u003c\/td\u003e\n\u003c\/tr\u003e\n \u003ctr\u003e\n\u003ctd\u003eKey approach\u003c\/td\u003e\n\u003ctd\u003eInclude heterogeneity parameters in tests and power calculations\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eOur Verdict\u003c\/h2\u003e\n\u003cp\u003eHeterogeneity in Statistical Genetics is a focused, methodical resource for practitioners who must model mixtures in genetic association studies; it offers valuable, practical guidance on including heterogeneity in tests and planning. For its intended audience it represents good value because it addresses a common but often overlooked issue with targeted statistical solutions.\u003c\/p\u003e\n\n\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003eDoes this book cover practical sample size calculations for mixed populations?\u003c\/strong\u003e\u003cbr\u003eYes. A core message is that sample size and power calculations should include at least one heterogeneity parameter, and the book documents methods to do so.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eIs this suitable for beginners in genetics?\u003c\/strong\u003e\u003cbr\u003eNo. The treatment is technical and assumes familiarity with statistical testing and study design rather than introductory genetics concepts.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAre methods applicable to genomic as well as genetic association data?\u003c\/strong\u003e\u003cbr\u003eYes. The authors state methods are intended for genetic and genomic association data where mixtures are present.\u003c\/p\u003e","brand":"Derek Gordon, Stephen J. Finch, Wonkuk Kim","offers":[{"title":"Default Title","offer_id":48616452358363,"sku":"303061123X","price":111.28,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/61B1T5zdyIL._SL1254.jpg?v=1778505345","url":"https:\/\/gearmusthave.com\/products\/heterogeneity-in-statistical-genetics-how-to-assess-address","provider":"GearMustHave","version":"1.0","type":"link"}