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Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence | 
 enlarge | Authors: Judith D. Singer, John B. Willett
Publisher: Oxford University Press, USA
Category: Book
List Price: $72.95
Buy New: $54.99
You Save: $17.96 (25%)
New (29) Used (10) from $54.99
Rating:  11 reviews
Sales Rank: 40480
Media: Hardcover
Edition: 1
Pages: 672
Number Of Items: 1
Shipping Weight (lbs): 1.7
Dimensions (in): 9.3 x 6.5 x 1.5
ISBN: 0195152964
Dewey Decimal Number: 001.42
EAN: 9780195152968
ASIN: 0195152964
Publication Date: March 27, 2003
Availability: Usually ships in 1-2 business days
Shipping: Expedited shipping available
Shipping: International shipping available
Condition: Brand new in excellent condition. Ready to ship. Receive within 4 days. Satisfaction guaranteed. International delivery within 7 days. US edition.
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Product Description
Here is a much-needed professional book that will instruct readers in the many new methodologies now at their disposal to make the best use of longitudinal data. This book explains how to select an appropriate method given a research question, including how to use both individual growth modeling and survival analysis. Throughout the chapters, the authors employ many cases and examples from a variety of disciplines, covering multilevel models, curvilinear and discontinuous change, in addition to discrete-time hazard models, continuous-time event occurrence, and Cox regression models. Using Longitudinal Data is a unique contribution to the literature on research methods and will be useful to a wide range of behavioral and social science researchers.
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| Customer Reviews: Read 6 more reviews...
It is THAT good December 16, 2008
I Teach Typing (Stanford, CA USA)
1 out of 1 found this review helpful
Others have have already said that this book is superb and I completely agree. If you have had a class that covers applied statistics (basic correlation and regression) you should be able to pick this up and read it with no trouble. There is math here but is is *well* explained and the algebra is always presented with a worked example.
The code at UCLA (sorry they will not let me post the link here) makes the incredibly good writing even more valuable because, not only will you understand the concepts behind Mixed Effects/Hierarchical Linear Models, you will be able to implement the ideas. If you already have some experience with Mixed Effects/HLM browse the code and you will quickly see this book covers a wide scope. I have worked with the SAS code a lot and even though the book is a bit old (by a programmer's standards) the code still works just fine.
While the book is written to be clear for non-mathemeticians, there are many "intermediate to advanced" statistical topics covered here. These are importantly areas which are typically unintelligible to non-statisticians or are glossed over or ignored by other authors. Here are some noteworthy examples. This book could/should be used as a text on data exploration and visualization. There are many case-studies throughout the book and they all begin with great visualizations (with the all important code supplements showing the novice how to make the plots in the book). Topics like fitting lines, splines, curves are covered clearly and are shown beautifully. The discussion on choosing between sets of models using deviance (-2log likelihood) and AIC has the best coverage of any book. The general discussion of likelihood estimation (maximum likelihood and restricted maximum likelihood) is superb. The coverage of data transformation for model fitting is explained well and is presented with wonderful plots. These "bonus" topics are interwoven into the great explanations of longitudinal data analyzes.
There is so much to like in this book and nothing to criticize (except perhaps the price). It makes the rest of the books in the field look bad.
A Wonderful Work July 15, 2007
Theodore Micceri (Florida)
2 out of 2 found this review helpful
I find Professor Singer's Book to be a most informative and useful tool for anyone who wishes to better understand Multilevel Modeling.
Applied Longitudinal Data Analysis by Singer,et al March 13, 2007
June Simakani
3 out of 3 found this review helpful
Clearly written text... and usefull for researchers.
I would recommend it to anyone starting to learn about the subject!
The Clearest and Most Useful Book on HLM for Longitudinal Studies July 27, 2006
M. Allen Greenbaum (California)
12 out of 12 found this review helpful
This is simply the best book for those analyzing longitudinal data (data measured at more than one time point). Singer's coverage of Hierarchical Linear MOdeling (HLM) is clear, well-written (sprinkled with humor, it's like a lecture by the most popular prof. at your school), and geared towards researchers who need their programs to run, not just learn the mathematical underpinnings. Singer and Willett (the coauthor, not listed above!) set the standard for presenting math/statistics book examples.
THe authors accomplish the latter by keying her examples to data located at a UCLA website; you can run the same programs on the same datasets used in the book (wow!), and compare your output, troubleshooting any problems you may have. Singer and Willett (her coauthor, not listed here!) provide outputs and programs correspoing to several of the most popular statistical programs, including SAS and SPSS.
SInger and Willet also explain the rationale for using HLM over more traditional techniques such as regression. Simply stated, regression aggregates at a level that cause one to lose information (and hence the power to detect differences.) HLM allows one to look at overall differences due to time, but also the trajectories of individual differences who are "nested" within those time points. It's the (relatively) new thing, and is increasing used by investigators, and desired by peer reviewers.
As supplements, I suggest using the UCLA website mentioned above, subscribing to an e-mail LISTSERV for interesting (though sometimes compicated discussions of "multilevel modeling" (MULTILEVEL@JISCMAIL.AC.UK), and searching for Judith Singer's website through Google or A9 (if you use A9--"Alexa"--enough you'll get a small discount at Amazon.com). Also, compare Amazon's and Judith Singer's (through her website) current prices on this book.
Breaking down complex analyses March 18, 2006
Margaret Kern (Riverside, CA USA)
2 out of 3 found this review helpful
This is an excellent book. Multilevel modeling and survival analysis are becoming increasingly important in psychological studies, but are pretty complicated procedures. Singer & Willet offer both a conceptual background and practical ways to do the analyses in a clear, understandable manner. The book is very readable and will be an important reference for future analyses!
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