Statistical Methods In Neuropsychology

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.

This bk integrates clinical experience w/the latest methods of statistical analysis to provide all who have professional stakes in the outcomes of assessment w/better methods of hypothesis-testing that will lead to more valid & reliable assessments of pa

The goal of the second edition is to introduce the advance undergraduate or graduate student and more seasoned research scientists in any of the allied health sciences to a wide array of methodological and biostatistical issues, as they occur in the context of both published and ongoing research. Some sixty-four articles published between 1992 and 2002 have been selected from the Journal of Clinical and Experimental Neuropsychology, The Clinical Neuropsychologist, and Child Neuropsychology and reproduced in this volume. While building upon a working knowledge and understanding of the basic univariate data analytic techniques and the research designs to which they apply, the approach to the more complex multivariate techniques is presented primarily at a conceptual and essentially non-mathematical level. While the issue of the complexity of some of the more recent and standard approaches to data analytic strategies, and their important role to specific research designs is important to convey, there remains an even more fundamental issue of whether the results of correctly applied data analytic strategies make any practical or clinical sense, above and beyond their having reached levels of "statistical significance". These critical issues are addressed throughout various commentaries that the editors make at appropriate points in the text. The volume will appeal to advanced undergraduate and graduate students as well as clinical neuropsychologists and research scientists in any of the allied health disciplines.

This book has been written to meet several needs. Firstly there is a need for a book which integrates statistics, research design, ex periments and report writing so that none is learned in a vacuum, as commonly is the case, isolated from the others. The aim is to make the student an active learner encouraged to carry out experiments, so ex periencing and understanding the design problems and statistical analyses in the practical context where he can see exactly what he is doing and why. The aim is that by the end of the book, the student should be able to evaluate the research of others, to define a problem, formulate a hypothesis about it, design and carry out the experiment, apply the correct statistics, discuss the results and implications, and write it all up in a logical and sensible fashion. The principle is that old pedagogic one of learning by doing. Secondly, there is a need for an introductory text on statistics, research design and experimental work for the many students who meet psychology and social science for the first time. The initiate in behavioural science needs to gain a conceptual understanding of statistical procedures and design techniques in order to carry out his own investigations and to understand and evaluate constructively the investigations of others. However, experience has shown us that many students (and even some fellow teachers) are somewhat reluctant to study this area as they believe it is difficult and involves mathematics.

​​ ​Cluster analysis is a multivariate classification technique that allows for identification of homogenous subgroups within diverse samples based on shared characteristics. In recent years, cluster analysis has been increasingly applied to psychological and neuropsychological variables to address a number of empirical questions. This book provides an overview of cluster analysis, including statistical and methodological considerations in its application to neurobehavioral variables. First, an introduction to cluster analysis is presented that emphasizes issues of relevance to neuropsychological research, including controversies surrounding it use. Cluster analysis is then applied to clinical disorders that do not have an associated prototypical neuropsychological profile, including traumatic brain injury, schizophrenia, and health problems associated with homelessness. In a second application, cluster analysis is used to investigate the course of normal memory development. Finally, cluster analysis is applied to classification of brain injury severity in children and adolescents who sustained traumatic brain injury.

No other book reviews clinical neuropsychological assessment from an empirical psychometric perspective. In this completely revised and updated 2nd edition, the concepts and methods of psychometric neuropsychology are presented as a framework by which to evaluate current instruments. Newer methodologies and statistical techniques are discussed, such as meta analysis, effect size, confirming factor analysis and ecological validity. The explosion of research in this area since the publication of the first edition in 1989, has been incorporated, including a greatly expanded chapter on child assessment instruments. This volume is a must for the bookshelf of every clinical neuropsychologist as well as researchers and students. Anyone conducting forensic evaluations will especially find useful the information on reliability and validity when preparing for court appearances.

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