자료유형 | 학위논문 |
---|---|
서명/저자사항 | Marginally Interpretable Generalized Linear Mixed Models. |
개인저자 | Gory, Jeffrey J. |
단체저자명 | The Ohio State University. Statistics. |
발행사항 | [S.l.]: The Ohio State University., 2017. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2017. |
형태사항 | 178 p. |
기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
ISBN | 9780438309739 |
학위논문주기 | Thesis (Ph.D.)--The Ohio State University, 2017. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Advisers: Peter Craigmile |
요약 | A popular approach for relating correlated measurements of a non-Gaussian response variable to a set of predictors is to introduce latent random variables and fit a generalized linear mixed model. The conventional strategy for specifying such a |
요약 | We define a class of marginally interpretable generalized linear mixed models that lead to parameter estimates with a marginal interpretation while maintaining the desirable statistical properties of a conditionally specified model. The distingu |
일반주제명 | Statistics. |
언어 | 영어 |
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