Journal ArticleDOI
Random-effects regression analysis of correlated grouped-time survival data.
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Random-effects regression modelling is proposed for analysis of correlated grouped-time survival data and a full-information maximum marginal likelihood solution is implemented using numerical quadrature to integrate over the distribution of multiple random effects.Citations
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Design and analysis of group-randomized trials: a review of recent methodological developments.
TL;DR: Developments in estimates of intraclass correlation, power analysis, matched designs, designs involving one group per condition, and designs in which individuals are randomized to receive treatments in groups are reviewed.
Journal ArticleDOI
Adjustments for Center in Multicenter Studies: An Overview
TL;DR: The inattention of published studies to departures from the assumption behind most statistical methods, the independence of observations, is overlooked, and investigators need to identify centers, incorporate the concept of centers into their designs, estimate the design effect, and adjust confidence intervals and P values appropriately.
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Initial Manifestations of Frailty Criteria and the Development of Frailty Phenotype in the Women's Health and Aging Study II
TL;DR: It is suggested that weakness may serve as a warning sign of increasing vulnerability in early frailty development, and weight loss and exhaustion may help to identify women most at risk for rapid adverse progression.
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Individual Covariation in Life‐History Traits: Seeing the Trees Despite the Forest
TL;DR: The results provided confirmation of what has been suggested by other investigators: within‐cohort phenotypic selection can mask senescence, and the development of models permitting access to individual variation in fitness is a promising advance for the study ofsenescence and evolutionary processes.
References
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Book
Hierarchical Linear Models: Applications and Data Analysis Methods
TL;DR: The Logic of Hierarchical Linear Models (LMLM) as discussed by the authors is a general framework for estimating and hypothesis testing for hierarchical linear models, and it has been used in many applications.
Journal ArticleDOI
Hierarchical Linear Models: Applications and Data Analysis Methods.
TL;DR: This chapter discusses Hierarchical Linear Models in Applications, Applications in Organizational Research, and Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known.
Journal ArticleDOI
Longitudinal data analysis using generalized linear models
Kung Yee Liang,Scott L. Zeger +1 more
TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.
Journal ArticleDOI
Categorical Data Analysis
TL;DR: In this article, categorical data analysis was used for categorical classification of categorical categorical datasets.Categorical Data Analysis, categorical Data analysis, CDA, CPDA, CDSA
Book
Analysis of Survival Data
David Cox,D. Oakes +1 more
TL;DR: In this article, the authors give a concise account of the analysis of survival data, focusing on new theory on the relationship between survival factors and identified explanatory variables and conclude with bibliographic notes and further results that can be used for student exercises.