資料來源: Google Book
Ordinal measurement in the behavioral sciences
- 作者: Cliff, Norman,
- 其他作者: Keats, J. A.
- 出版: Mahwah, N.J. : Lawrence Erlbaum Associates 2003.
- 稽核項: 1 online resource (x, 230 pages) :illustrations.
- 標題: Statistical methods. , Psychology , Psychological tests Statistical methods. , PSYCHOLOGY Statistics. , Electronic book. , Social sciences Statistical methods. , Psychology Mathematical models. , PSYCHOLOGY , Mathematical models. , Psychological tests , Electronic books. , Social sciences , Statistics. , Analysis of variance.
- ISBN: 0805820930 , 9780805820935
- ISBN: 0805820930
- 試查全文@TNUA:
- 附註: Includes bibliographical references (pages 212-217) and indexes.
- 摘要: This book provides an alternative method for measuring individual differences in psychological, educational, and other behavioral sciences studies. It is based on the assumptions of ordinal statistics as explained in Norman Cliff's 1996 Ordinal Methods for Behavioral Data Analysis. It provides the necessary background on ordinal measurement to permit its use to assess psychological and psychophysical tests and scales and interpret the data obtained. The authors believe that some of the behavioral measurement models used today do not fit the data or are inherently self-contradictory. App.
- 電子資源: https://dbs.tnua.edu.tw/login?url=https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=79441
- 系統號: 005300783
- 資料類型: 電子書
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- 引用網址: 複製連結
This book provides an alternative method for measuring individual differences in psychological, educational, and other behavioral sciences studies. It is based on the assumptions of ordinal statistics as explained in Norman Cliff's 1996 Ordinal Methods for Behavioral Data Analysis. It provides the necessary background on ordinal measurement to permit its use to assess psychological and psychophysical tests and scales and interpret the data obtained. The authors believe that some of the behavioral measurement models used today do not fit the data or are inherently self-contradictory. Applications of these models can therefore lead to unwarranted inferences regarding the status of the derived variables. These methods can also be difficult to apply, particularly in small-sample contexts without making additional, unrealistic assumptions. Ordinal methods more closely reflect the original data, are simple to apply, and can be used in samples of any size. The book's approach is in essence a return to simple empiricism in psychological measurement. Ordinal Measurement in the Behavioral Sciences provides: *methods for analyzing test responses; *extensive discussions of ordinal approaches to analyzing data that are judgments of stimuli; *methods for treating psychological data in ways consistent with its ordinal nature so as to stimulate new developments in this area; and *ordinal test theory and the unfolding methods that are applicable to cross-cultural studies. Advanced students, researchers, and practitioners concerned with psychological measurement should find this book relevant. Measurement professionals will find it provides useful and simple methods that stimulate thought about measurement's real issues.
來源: Google Book
來源: Google Book
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