Introduction to nonparametric item response theory
著者
書誌事項
Introduction to nonparametric item response theory
(Measurement methods for the social sciences series, v. 5)
Sage Publications, c2002
- : hbk
- : pbk
大学図書館所蔵 全19件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references (p. 157-164) and index
内容説明・目次
内容説明
"This manuscript addresses an important and complex topic in test development in a manner that is precise and accurate, yet very accessible to students and practitioners with a modest background in classical test theory and item response theory. It also provides an excellent introduction to nonparametric IRT models for the more mathematically sophisticated student or faculty member who will welcome the extensive additional reading lists that are found at the conclusion of each chapter."
-LINDA F. WIGHTMAN, School of Education, University of N. Carolina, Greensboro
"I thoroughly enjoyed this book, and liked the clear way the authors have worked through the chapters and examples. There are rich examples with plenty of exercises that encouraged me to try these methods with my own data. The quality of the interpretation is rich, particularly in the polytomous item domain. It is well worth having on the shelf as a reference tool and as available for graduate students who wish to know more."
-JOHN HATTIE, Head of the School of Education, University of Auckland, NZ
This book introduces social and behavioral science students and researchers to the theory and practice of the highly powerful methods of nonparametric item response theory (IRT). Anyone who uses or constructs tests or questionnaires for measuring abilities, achievements, personality traits, attitudes, or opinions will find nonparametric IRT useful for designing and improving such measurements. The authors show how the broadness of the nonparametric item response models allows them to fit many data sets and remain powerful enough for implying useful measurement properties, such as the ordering of persons using the simple total score (number-correct for dichotomous item tests and sum of rating scale score for polytomous item tests) and the ordering of the items using the item means. Many data analysis examples are given in the book, and a user-friendly computer program used throughout the book supports data analysis using nonparametric IRT. Given the importance of school admissions, certification, personnel selection, marketing, social policy evaluation, quality-of-life measurements, and assessments of deviant behavior, this book is a must read for students or researchers engaged in this work.
目次
Models for Mental Measurement / Philosophy and Assumptions Underlying Nonparametric IRT Models for Dichotomous Item Scores / The Monotone Homogeneity Model Applied to Transitive Reasoning Data / The Monotone Homogeneity Model: Concepts and Procedures / Automated Item Selection Under the Monotone Homogeneity Model / The Double Monotonicity Model / Extension of Nonparametric IRT to Polytomous Item Scores / Item Analysis Using Nonparametric IRT for Polytomous Items
「Nielsen BookData」 より