书目名称 | The Kernel Method of Test Equating |
编辑 | Alina A. Davier,Paul W. Holland,Dorothy T. Thayer |
视频video | http://file.papertrans.cn/913/912595/912595.mp4 |
丛书名称 | Statistics for Social and Behavioral Sciences |
图书封面 |  |
描述 | .Kernel Equating (KE) is a powerful, modern and unified approach to test equating. It is based on a flexible family of equipercentile-like equating functions and contains the linear equating function as a special case. Any equipercentile equating method has five steps or parts. They are: 1) pre-smoothing; 2) estimation of the score-probabilities on the target population; 3) continuization; 4) computing and diagnosing the equating function; 5) computing the standard error of equating and related accuracy measures. KE brings these steps together in an organized whole rather than treating them as disparate problems....KE exploits pre-smoothing by fitting log-linear models to score data, and incorporates it into step 5) above. KE provides new tools for diagnosing a given equating function, and for comparing two or more equating functions in order to choose between them. In this book, KE is applied to the four major equating designs and to both Chain Equating and Post-Stratification Equating for the Non-Equivalent groups with Anchor Test Design....This book will be an important reference for several groups: (a) Statisticians and others interested in the theory behind equating methods an |
出版日期 | Book 2004 |
关键词 | Excel; Fitting; NEAT design; Nation; Passing; data analysis; gaussian kernel smoothing; kernel equating; lon |
版次 | 1 |
doi | https://doi.org/10.1007/b97446 |
isbn_softcover | 978-1-4757-8098-7 |
isbn_ebook | 978-0-387-21719-2Series ISSN 2199-7357 Series E-ISSN 2199-7365 |
issn_series | 2199-7357 |
copyright | Springer Science+Business Media New York 2004 |