Advanced and Multivariate Statistical Methods: Practical Application and Interpretation

This book has nice checklists to follow for doing statistical analysis and detailed examples but it still involves the theory behind the stats. It is also relatively cheap. If you buy this book, you should get another book too because it can be hard to understand at times. Overall, a good book.

First, there are a lot of books on Statistical Methods and on SPSS and they can help when used in conjunction with this book. This book covers the following: It provides (1) an overview, (2) a guide to the techniques, (3) pre-data screening, (4) factor analysis (I love that procedure because it helps SOOO much), (5)AnCOVA, (6)MANOVA (true Manova - even though SPSS calls all syntax commands MANOVA), (7)Multiple Regression, (8)Path Analysis, (9)Factor Analysis, (10)DFA, (11)and Logistical Regression. Two of the best books out there to look at when using this book are Kachigan's Multivariate Statistical Analysis and Huck's Reading Statistics and Research because they fill in a lot more of the puzzle. The thing is that many books leave out specific things when you are trying to (1) learn how to use SPSS and how to play with different statistical methods and (2) many DO NOT tell you how to report what you find. In APA style the last one is something of a nail in the proverbial coffin, and if you are a student it could cost you time and make you wonder about the little lines of stylized red tape when you try to report you findings. That's where Mertler is beautiful and why the book is a great thing. In the pages of this book you will find (1) descriptions on specific methods that are more overviews than heavy introductions to methods, (2) key commands on how to feed data into SPSS and how to read what comes out, and (3) the way you should report everything you find when you read through your report. This does not mean there are not gaps in some of the reading; Discriminant Function Analysis (PG 301) made me wonder exactly how you were supposed to plug in new-comers to your formulas IF the Test of Equality of Group Means finds a low Significance BUT the Table of Steps does not exclude it. THAT was why I included the other books listed, because this book is more like a tool that helps you plug in something, pull out data, read it, and tell an audience what it all means. Huck and Kachigan make something of a wall to protect against any other problems BUT this book is a beautiful source when you need to plug in obscure testing methods. If you think you need this book then you probably do, and the price is well worth what it costs just to divulge some of the riddles that SPSS offers. If you specifically need to fill in the basics (parametric measures) with your SPSS then you might want to also include Zagumny's "The SPSS book" just to give you a complete overview of SPSS as a humanity's tool and help you make it the thing that can be your best statistical friend. This book is highly recommended and the other books listed here are as well.

This book is an excellent resource for individuals just starting with multivariate statistics and for those needing quick tips on test assumptions or help performing SPSS procedures and interpreting SPSS output. Despite its "Advanced" title, this book covers the basics of multivariate statistics. It reviews the basic applications, data assumptions, limitations, basic rationale and sample research questions for several multivariate methods including linear and logistic regression, ANOVA/ANCOVA, MANOVA/MANCOVA, factor analysis, and more. It also provides information on how to interpret SPSS output and how write up results. The focus is application, not statistical theory or proofs.Particularily helpful are step-by-step SPSS tips and the chapter on pre-analysis data screening.