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

Van der Elst, Wim

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Book Information
Edition:	1st
Publisher:	Springer Nature
ISBN:	3-031-50950-1 (3031509501)
ISBN-13:	978-3-031-50950-6 (9783031509506)
Binding:	Hardcover
Copyright:	2024
Weight:	0.00 Lbs.
Pages:	482
Subject Class:	PSY (Psychiatry and Psychology)
Remarks:	This Title is Not Yet Published, Scheduled to Release 05/04/24
Return Policy:	Returns accepted up to 12 months provided no other recalls or return restrictions apply.

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Abstract:

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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