UID:
almafu_9959241331102883
Format:
1 online resource (xi, 267 pages) :
,
digital, PDF file(s).
ISBN:
1-107-16872-4
,
0-521-68126-X
,
1-280-85038-8
,
0-511-27855-1
,
0-511-27738-5
,
0-511-32143-0
,
0-511-61876-X
,
0-511-27797-0
Content:
The measurement models employed to score tests have been evolving over the past century from those that focus on the entire test (true score theory) to models that focus on individual test items (item response theory) to models that use small groups of items (testlets) as the fungible unit from which tests are constructed and scored (testlet response theory, or TRT). In this book, the inventors of TRT trace the history of this evolution and explain the character of modern TRT. Written for researchers and professionals in statistics, psychometrics, and educational psychology, the first part offers an accessible introduction to TRT and its applications. The second part presents a comprehensive, self-contained discussion of the model couched within a fully Bayesian framework. Its parameters are estimated using Markov chain Monte Carlo procedures, and the resulting posterior distributions of the parameter estimates yield insights into score stability that were previously unsuspected.
Note:
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
,
Cover; Half-title; Title; Copyright; Dedication; Contents; Preface; PART I Introduction to Testlets; 1 Introduction; 2 True score theory; 3 Item response theory; 4 What's a testlet and why do we need them?; 5 The origins of testlet response theory - three alternatives; 6 Fitting testlets with polytomous IRT models; PART II Bayesian testlet response theory; Recapitulation and introduction; 7 A brief history and the basic ideas of modern testlet response theory; 8 The 2-PL Bayesian testlet model; 9 The 3-PL Bayesian testlet model
,
10 A Bayesian testlet model for a mixture of binary and polytomous data11 A Bayesian testlet model with covariates; 12 Testlet nonresponse theory: dealing with missing data; PART III Two applications and a tutorial; 13 Using posterior distributions to evaluate passing scores: the PPoP curve; 14 A Bayesian method for studying DIF: cautionary tale filled with surprises and delights; 15 A Bayesian primer; Glossary of terms; Epilogue; Bibliography; Author Index; Subject Index
,
English
Additional Edition:
ISBN 0-511-27915-9
Additional Edition:
ISBN 0-521-86272-8
Language:
English
URL:
https://doi.org/10.1017/CBO9780511618765
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