Multilevel and Longitudinal Modeling Using Stata, Volumes I and II, Third Edition

a leader in this field , clear and usable

Great content. The index in this book is weak weak weak.

It's a good book nonetheless disappointed in one aspect: ignores modeling when the dependent variable consists of plausible values ​​such as database as TIMSS and PISA.

This is a very impressive and useful book. It strikes an excellent balance between theory and application and is very well-written. Even non-users of Stata will find it an excellent, detailed overview of a set of important and complex topics.

I really like this book. Although it is still difficult material to process, the authors do a good job explaining things.

This book is beneficial for someone who needs to improve their understanding of mixed model analysis using complex interaction terms.

Thanks

The first edition of Rabe-Hesketh and Skrondal's "Multilevel and Longitudinal ModelingUsing Stata" was published in 2005. The second edition was released in 2008, and now thisthird edition in 2012. With each edition the scope of the model's discussed in the texthas increased. This release is in fact a 2-volume work, with the first volume devoted topanel models having a continuous response (or dependent variable), and the second todiscrete response panel models.Nearly every panel model in the literature is addressed in the text. Discussion beginswith a review of basic linear regression and provides the basics upon which more complexmodels will be developed. Then variance-components are addressed, explaining concepts suchas between-subject heterogeneity and within-subject dependence. Following this the authorsintroduce fixed and random effects models, and then delve into the details of both randomintercept and random coefficient models. Mixed effects models is given a thorough examination.Following a discussion of subject-specific models, the authors turn to population-averagedor marginal models, as well as growth curve models. The first volume concludes with chaptersdevoted to higher-level models with nested random effects and crossed random effects mdoels.Throughout the volume each model, where appropriate, is approached as one, two, and higherlevel models.Volume two addresses one, two, and higher level categorical response models, count models,and survival or duration models. The emphasis, of course, is on understanding data thatis structured as panels - whether clustered or longitudinal. Zero-inflated count models,for example, are not discussed, nor are generalized binomial, generalized Poisson, orgeneralized negative binomial models. But near every type of categorical response panel modelis discussed -- in full.Volume one is over 500 pages in length; volume two is a bit shorter. Together the two volumesconsist of 974 pages plus nearly 40 Roman numeral pages. Stata statistical software is usedthroughout the text, which is dually published by Stata Press and Chapman & Hall/CRC. Stataand Limdep econometric software are in my opinion the two most compehensive panel-modelingstatistical packages available, with SAS the next best in this regard. Stata, as a generalpurpose stat package has a much wider range of capabilities, as does SAS. It is therefore avery good choice of software to use for examining this class of models. It is also a comparativelyeasy programming language. The authors have written 'gllamm', a Stata command that allows estimationof many of the more complex models disussed in the text, including, for example, athree-level random coefficient logistic regression model. Most examples though rely on Stata'sbuilt-in commands, plus it's Mata matrix programming facility.This two-volume work is in my opinion the foremost text on multilevel models.It uses Stata for examples, but any text that uses examples to explain difficult statisticalconcepts and methods needs to use some type of statistical software. Stata is ideal for thistype of modeling, so has been used in this text. Researchers who use other software formodeling; eg SAS, R, SPSS, etc, can use the methods taught in this volume with their preferredpackage, insofar as it has the capability to estimate a particular type of model.I highly recommend this two-volume set of books to anyone with an interest in modelingmultilevel and longitudial models, regardless of their preferred statistical software. It isthe most comprehensive work available on applied multilevel modeling. It is also very wellwritten, with each model examined in a very clear manner. Data sets and author-written code isprovided on the book's web site. Readers therefore are able to replicate the exmaples in the book,or to adapt them for their own projects.

The book is wonderfully written with an excellent strategy, combining synthetic notes on statistical concepts and a clear step by step on Stata analyses.

Very informative. Well-written.

Very fast delivery and the books are excellent!

Very good book