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Titlebook: Marginal Models; For Dependent, Clust Jacques A.‘Hagenaars,Marcel A. Croon,Wicher Bergsm Book 2009 Springer-Verlag New York 2009 Fitting.In

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書目名稱Marginal Models
副標(biāo)題For Dependent, Clust
編輯Jacques A.‘Hagenaars,Marcel A. Croon,Wicher Bergsm
視頻videohttp://file.papertrans.cn/624/623870/623870.mp4
概述Includes supplementary material:
叢書名稱Statistics for Social and Behavioral Sciences
圖書封面Titlebook: Marginal Models; For Dependent, Clust Jacques A.‘Hagenaars,Marcel A. Croon,Wicher Bergsm Book 2009 Springer-Verlag New York 2009 Fitting.In
描述.Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles of marginal modeling and offers a wide range of possible applications. Marginal models are often the best choice for answering important research questions when dependent observations are involved, as the many real world examples in this book show...In the social, behavioral, educational, economic, and biomedical sciences, data are often collected in ways that introduce dependencies in the observations to be compared. For example, the same respondents are interviewed at several occasions, several members of networks or groups are interviewed within the same survey, or, within families, both children and parents are investigated. Statistical methods that take the dependencies in the data into account must then be used, e.g., when observations at time one and time two are compared in longitudinal studies. At present, researchers almost automatically turn to multi-level models or to GEE estimation to deal with these dependencies. Despite the enormous potential and applicability of these recent developments, they require restrictive assumptions on the n
出版日期Book 2009
關(guān)鍵詞Fitting; Interview; Likelihood; calculus; categorical data; correlated observations; dependent observation
版次1
doihttps://doi.org/10.1007/b12532
isbn_softcover978-1-4419-1873-4
isbn_ebook978-0-387-09610-0Series ISSN 2199-7357 Series E-ISSN 2199-7365
issn_series 2199-7357
copyrightSpringer-Verlag New York 2009
The information of publication is updating

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Statistics for Social and Behavioral Scienceshttp://image.papertrans.cn/m/image/623870.jpg
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978-1-4419-1873-4Springer-Verlag New York 2009
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2199-7357 i-level models or to GEE estimation to deal with these dependencies. Despite the enormous potential and applicability of these recent developments, they require restrictive assumptions on the n978-1-4419-1873-4978-0-387-09610-0Series ISSN 2199-7357 Series E-ISSN 2199-7365
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rk is that of cellular differentiation from omnipotent ES cells to terminally differentiated cells. Insight into this network is the basis for reprogramming of cells and the creation of iPS cells. An alternative example of a transcription factor network is that of NFKB and its regulation by IKBK pro
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Wicher Bergsma,Marcel Croon,Jacques A. Hagenaars. Transcription factories function as some sort of a “magnet” for commonly regulated genes with shared nuclear positions. This suggests that the transcriptional status of a gene is based on its position in the nucleus sphere. The transcription factory model is important for:.In this chapter, we will
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