Regression-Based Normative Data for Psychological Assessment: A Hands-On Approach Using R - Couverture souple

Van Der Elst, Wim

 
9783031509537: Regression-Based Normative Data for Psychological Assessment: A Hands-On Approach Using R

Synopsis

Over the last 20 years, so-called regression-based normative methods have become increasingly popular. In this approach, regression models for the mean and the residual variance structure are used to derive the normative data. The regression-based normative approach has some important advantages over the traditional normative approach, e.g., it allows for deriving more fine-grained norms and typically requires a substantially smaller sample size to derive accurate norms.

This book focuses on regression-based methods to derive normative data. The target audience are psychologists and other researchers in the behavioral sciences who are interested in deriving normative data for psychological tests (e.g., cognitive tests, questionnaires, rating scales, etc.). The book provides the essential theoretical background that is needed to understand the methodology, with a strong emphasis on the practical/real-life application of the methodology. To this end, the book is also accompanied by an open-source software package (the R library NormData) that is used to exemplify how normative data can be derived in several case studies.


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À propos de l?auteur

Wim Van der Elst (PhD) has a background in psychology and statistics, and is currently employed as a statistician in the pharmaceutical industry. He has published extensively on regression-based normative data, psychometrics, psychological assessment, and the statistical evaluation of biomarkers. He is also the lead programmer of several R libraries.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Autres éditions populaires du même titre

9783031509506: Regression-based Normative Data for Psychological Assessment: A Hands-on Approach Using R

Edition présentée

ISBN 10 :  3031509501 ISBN 13 :  9783031509506
Editeur : Springer International Publishin..., 2024
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