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Multilevel and Longitudinal Modeling Using Stata, Volumes I and II
This book examines Stata's treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are "mixed" because they allow fixed and random effects, and they are "generalized" because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables. Volume I covers continuous Gaussian linear mixed models and has nine chapters. The chapters are organized in four parts. Volume II discusses generalized linear mixed models for binary, categorical, count, and survival outcomes.
2 pages, Paperback
First published April 2, 2012
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December 29, 2014
If you are a Stata user and have some statistics background, you'll find these books fairly accessible. I think anyone wanting to explore multilevel modeling (MLM) should pick these up. They're relevant for a variety of backgrounds and program users, but use a different vocabulary than Snijders and Bosker .
These books provide an overview of some stats concepts needed for MLM and do a good job of walking the reader through a variety of methods and examples. They are very readable books, especially if you know a little about MLM, but the authors do get very technical on occasion (statistically speaking). The books fluctuate between being too technical and being clear/universally relevant.
The books have good coverage of MLM concepts, but I found myself wanting more information and more examples, especially in the context of longitudinal data, for: non-ordinal multinomial outcomes, how to select covariance structures, using covariance vs. residual structures, and negative binomial/overdispersed outcomes. I do understand that, with the exception of covariance structures, these can be tough topics and beyond the scope of most readers' goals.
These books make some reference to the "gllamm" command, but do not focus on it (as it's becoming outdated). If you want to learn more specifically about that, these aren't the books you want.
These books provide an overview of some stats concepts needed for MLM and do a good job of walking the reader through a variety of methods and examples. They are very readable books, especially if you know a little about MLM, but the authors do get very technical on occasion (statistically speaking). The books fluctuate between being too technical and being clear/universally relevant.
The books have good coverage of MLM concepts, but I found myself wanting more information and more examples, especially in the context of longitudinal data, for: non-ordinal multinomial outcomes, how to select covariance structures, using covariance vs. residual structures, and negative binomial/overdispersed outcomes. I do understand that, with the exception of covariance structures, these can be tough topics and beyond the scope of most readers' goals.
These books make some reference to the "gllamm" command, but do not focus on it (as it's becoming outdated). If you want to learn more specifically about that, these aren't the books you want.
Displaying 1 of 1 review