Main description:

This book describes appropriate statistical models that are commonly utilized in neuropsychology. The book discusses such issues as developing normative data for neuropsychological measures, assessing the validity of neuropsychological tests, and quantifying change “over time” through longitudinal analyses. The rationale for and allure of the volume is the fact that there are no publications that dovetail the two subdisciplines of applied statistics and neuropsychology. The overall objective of this book is to provide a pragmatic and concrete source for applying methodological and statistical techniques in research studies whose emphasis includes neuropsychology. Since there are a plethora of technique to arrive at similar answers, each method with its strengths and weaknesses will be delineated. The beauty of the book will be that it will hopefully demystify commonly encountered issues faced with researchers. More specifically, it will provide a “how to do it” approach.

Feature:

Addresses the issue of when and how to use appropriate statistical modeling in neuropsychology

Only text to dovetail the two subdisciplines of neuropsychology and statistical modeling through nonmathematical frameworks

Provides a how-to approach to overcoming common problems in neuropsychology research

Back cover:

Statistical Methods in Neuropsychology

Common Procedures Made Comprehensible

David Aaron Maroof

 Statistics: not only the bane of many a student’s existence, but also puzzling to any number of mental health professionals. At the same time, they are necessary in making sound clinical judgments as to clients’ cognitive functioning or decline. Without them, a practitioner may be at a loss to explain findings or recommendations, or understand data in context.
 
The first publication of its kind, Statistical Methods in Neuropsychology brings the broad field of applied statistics and the specialized field of neuropsychology together to simplify and demystify test results. In readable, at times downright funny prose employing the minimum of hard math (and even less hard jargon), this concise volume shows readers how to effectively translate psychometric test data into real-world clinical practice, and offers a fuller understanding of the research literature. The author critiques commonly used statistical methods on the basis of their strengths and weaknesses, and reviews the issues in these key areas:
 
• Assessing validity.
• Statistical assumptions.
• Exploratory factor analysis.
• Normative data.
• Covariates and covariance analysis.
• Regression and logistic regression analysis.
• Multivariate analysis of variance.
 
Statistical Methods in Neuropsychology will appeal to a wide variety of neuropsychologists, cognitive neuroscientists, psychiatrists, and experimental psychologists: those who understand statistics but want to know the why behind them, those new to the field and still getting familiar with the formulas, and those wishing to retake the course with a witty, world-class professor.