Multilevel and Longitudinal Modeling with IBM SPSS (Quantitative Methodology Series)

I'm an entrepreneurship professor that does research on startups. While I'm a subject-matter expert on the startup process, I'm not a statistician. So while I can handle traditional statistical analysis, I delved into the scary world of multi-level longitudinal analysis with a great deal of trepidation and only out of absolute necessity. This book was a god-send, and is in my opinion, the model that all such books should follow. First, it's written in regular English, not indecipherable statistics-speak. It walks readers through many detailed examples, explaining why things are done, what choices should be made, and shows you how to do the analysis, step-by-step in SPSS. Each example is followed by a clear "Interpreting the Output" explanation. Having said that, this is a book on sophisticated statistical analysis, so a careful reading is necessary. Chapters 1 -4 demonstrate the development of multi-level models (with examples) for cross-sectional data. Chapters 5 and beyond does the same with repeated measures (longitudinal) data. My copy now has bookmarks, high-lights and/or written comments on nearly every page. Highly recommend.

Great workbook. Very well written and easy to follow. Provides invaluable help for those who are willing to learn analyses on their own. Discussion of statistical topics includes the basics but also clearly describes and illustrates more complex topics for those of us who are not experts. Examples are really helpful. I highly recommend this workbook.

The book is full of great examples and clear explanations. The data sets that were provided are very helpful, both in following along with the text and constructing your own data sets for your own research questions. I've recommended it to many students.

The content of this book is very useful. It gives a comprehensive guidance in preparing data and conducting the analysis. The guidance is easily comprehend and very helpful.

good practical guide

Really enjoy the way the author presents MLM, enough conceptual information to understand the underlying processes, while also presenting SA drills to facilitate computation. I would purchase other books from Heck

An easy to follow text on multilevel modelling that is of great value to the practitioner.

After trying multiple times to use this book I have to say that it is not that helpful. Multilevel modeling is complicated to grasp, and turning the explanatory model into an actual analysis is a key bridge. Unfortunately, that seems to be where this book falls short. It goes over and over principles that, once you understand them, become tedious to wade through. At times it goes into the minutiae of co-variance matrices etc. without explaining why one might use one vs. the other in any practical situations. Finally, when it goes through implementing examples in SPSS it wastes pages upon pages with pictures of clicking on this button and opening that menu, etc. Again, once you know how the procedure works, that becomes wasteful. Instead, it would be helpful to include WHY one clicks on a certain button but completely ignores 70% of the options. I think it might be better to read a book on theory, like those often reference within this book, and then learn the syntax version of SPSS to perform the operations on ones own.