Measurement, Design, and Analysis: An Integrated Approach

I assign this book in my graduate psychology research methods seminar. I also supplement the book with original sources, but I like to have my students read the relevant chapters from P & S first, as it provides a well-written overview and framework for integrating the articles they read subsequently. I haven't found a textbook for graduate research methods that I've liked better, and believe me I've looked. The clarity of the writing is the greatest strength of the book. Chapters are written in an extremely easy to read manner, and they communicate difficult concepts clearly. I frequently get comments from my students such as "I didn't understand the multitrait-multimethod matrix article until I read the summary of it in Pedhazur & Schmelkin." My students also find the chapters on statistical analysis quite helpful, even though I don't cover that material in my class. I recommend this book strongly to anybody in the social sciences.

We used P & S (as we called it) in our PhD research methods seminar, and I still refer to it from time to time when I need to cite a source in research methodology. The intended audience of this book is definitely academic researchers and PhD students. Although I suppose a master's student with a concentration in quantitative methods might also find it useful. P & S are comprehensive in their coverage of research methodology, particularly quantitative methods, and associated research designs. I found their chapters on instrument development, construct validation, and experimental designs particularly useful. I also think P & S stands up well as compared to other similar works, such as Nunally, for instance. I keep both on my shelf, but I find Nunally more useful for cites that require a "rule of thumb" or justification of a particular research decision, while I find P & S more useful for "how to" aspects of research design or explanations of the many various procedures that quantitative researchers encounter in the course of their work. Overall, I would recommend this book as a valuable addition to the library of any academician or PhD student.

This outstanding textbook is a "One Stop Shop" for the majority of essential topics for researchers with a statistical background. Exhaustive. Personnel without an anaylitical/technical background may find it hard to use. As a reference for someone doing a Phd, it is a book you'll refer to again and again.

This is an essential book for anyone doing advanced postgraduate research (especially PhD level). It is quite heavy reading but is a definitive reference on the use, interpretation and reporting of statistics, including lots of little known information about effect size, sample sizes, statistical power not covered in standard texts. Best of all, it exposes lots of common misconceptions and mistakes committed in most published research - after reading this book, you will be amazed how often these mistakes are made even in papers published in top journals. You can be pretty sure that if you satisfy the (very rigorous) requirements of this book, that your thesis will get past any examiner!A statistics book written FOR researchers BY researchers (rather than statisticians)

This is a very wide-ranging work, covering elements of psychometrics as well as statistics to the level of structural equation models. The book has a nice introductory tone, and should be easily grasped by most graduate students. Some of the information on CFA and SEM is now a bit dated. I smiled when I read the other reviewer's comments about Pedhazur's notable cynicism; I share his cynical view, having seen a multitude of published papers that were just garbage because the analyses were not thoughtful. Pedhazur's cynicism should be seen as a warning, and not taken beyond that, in my opinion.