| 書目名稱 | Regression-Based Normative Data for Psychological Assessment | | 副標(biāo)題 | A Hands-On Approach | | 編輯 | Wim Van der Elst | | 視頻video | http://file.papertrans.cn/826/825523/825523.mp4 | | 概述 | Provides a solid introduction in regression-based normative methods without being overly technical.Comes with a comprehensive open-source software package to help efficiently derive regression-based n | | 圖書封面 |  | | 描述 | .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.. | | 出版日期 | Book 2024 | | 關(guān)鍵詞 | regression-based normative data; R software; norm-referenced scores; psychological assessment; normative | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-50951-3 | | isbn_softcover | 978-3-031-50953-7 | | isbn_ebook | 978-3-031-50951-3 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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