Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. Beyond these natural processes and events, external forces and interventions instigate and disrupt change: test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. Applied Longitudinal Data Analysis is a much-needed professional book for empirical researchers and graduate students in the behavioral, social, and biomedical sciences. It offers the first accessible in-depth presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using clear, concise prose and real data sets from published studies, the authors take you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models.
Applied Longitudinal Data Analysis offers readers a private consultation session with internationally recognized experts and represents a unique contribution to the literature on quantitative empirical methods.
Visit http://www.ats.ucla.edu/stat/examples/alda.htm for:
· Downloadable data sets
· Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more
· Additional material for data analysis
"synopsis" may belong to another edition of this title.
John B. Willett is at Harvard University.
"The book begins with an excellent introduction to the types of questions that might be answered by a longitudinal study...After a chapter with sensible suggestions for exploratory analysis... --Statistics in Medicine Review
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