http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
statistics for longitudinal and contextual analysis
xxix, 658 pages : illustrations ; 26 cm.
This comprehensive text introduces regression, the general linear model, structural equation modeling, the hierarchical linear model, growth curve models, panel data and event history models and includes discussion of published implementations of each technique showing how it was used to address substantive and interesting research questions. The text takes a step-by-step approach in the presentation of each topic, using mathematical derivations where necessary, but primarily emphasizing how the methods involved can be implemented, are used in addressing representative substantive problems than span a number of disciplines, and can be interpreted in words. Students often face the "What do I do now?" question. This book contains liberal advice about what to do in many situations. A recurring theme in the book is to emphasize the importance of using the "right" (better) model rather than simpler models that may often produce misleading results. Many examples start with the simple version, and proceed to show how results change when a more appropriate approach is used. In summary, this text occupies a unique niche, multiple and very popular topics, with an emphasis on the choices, strengths and limits and unique perspectives offered by each technique, relative to others. The book demonstrates the analyses in STATA and SAS.
A review of correlation and regression -- Generalizations of regression 1 : testing and interpreting interactions -- Generalizations of regression 2 : nonlinear regression -- Generalizations of regression 3 : logistic regression -- Generalizations of regression 4 : the generalized linear model -- From equations to models : the process of explanation -- An introduction to structural equation models -- Identification and testing of models -- Variations and extensions of SEM -- An introduction to hierarchical linear models -- The generalized hierarchical linear model -- Growth curve models -- Introduction to regression for panel data -- Variations and extensions of panel regression -- Event history analysis in discrete time -- The continuous time event history model.
Includes bibliographical references (pages 641-646) and index.