Models for Uncertainty in Educational Testing

Author:   Nicholas T. Longford
Publisher:   Springer-Verlag New York Inc.
Edition:   1995 ed.
ISBN:  

9780387945132


Pages:   285
Publication Date:   14 July 1995
Format:   Hardback
Availability:   Awaiting stock   Availability explained
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Models for Uncertainty in Educational Testing


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Overview

A theme running through this book is that of making inference about sources of variation or uncertainty, and the author shows how information about these sources can be used for improved estimation of certain elementary quantities. Amongst the topics covered are: essay rating, summarizing item-level properties, equating of tests, small-area estimation, and incomplete longitudinal studies. Throughout, examples are given using real data sets which exemplify these applications.

Full Product Details

Author:   Nicholas T. Longford
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   1995 ed.
Dimensions:   Width: 16.20cm , Height: 2.20cm , Length: 24.10cm
Weight:   0.605kg
ISBN:  

9780387945132


ISBN 10:   038794513
Pages:   285
Publication Date:   14 July 1995
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Awaiting stock   Availability explained
The supplier is currently out of stock of this item. It will be ordered for you and placed on backorder. Once it does come back in stock, we will ship it out for you.

Table of Contents

1 Inference about variation.- 1.1 Imperfection and variation.- 1.2 Educational measurement and testing.- 1.3 Statistical context.- 2 Reliability of essay rating.- 2.1 Introduction.- 2.2 Models.- 2.3 Estimation.- 2.4 Extensions.- 2.5 Diagnostic procedures.- 2.6 Examples.- 2.7 Standard errors.- 2.8 Summary.- 2.9 Literature review.- 3 Adjusting subjectively rated scores.- 3.1 Introduction.- 3.2 Estimating severity.- 3.3 Examinee-specific shrinkage.- 3.4 General scheme.- 3.5 More diagnostics.- 3.6 Examples.- 3.7 Estimating linear combinations of true scores.- 3.8 Summary.- Appendix. Derivation of MSE for the general adjustment scheme.- 4 Rating several essays.- 4.1 Introduction.- 4.2 Models.- 4.3 Estimation.- 4.4 Application.- 4.5 Choice of essay topics.- 4.6 Summary.- 5 Summarizing item-level properties.- 5.1 Introduction.- 5.2 Differential item functioning.- 5.3 DIF variance.- 5.4 Estimation.- 5.5 Examples.- 5.6 Shrinkage estimation of DIF coefficients.- 5.7 Model criticism and diagnostics.- 5.8 Multiple administrations.- 5.9 Conclusion.- 6 Equating and equivalence of tests.- 6.1 Introduction.- 6.2 Equivalent scores.- 6.3 Estimation.- 6.4 Application.- 6.5 Summary.- 7 Inference from surveys with complex sampling design.- 7.1 Introduction.- 7.2 Sampling design.- 7.3 Proficiency scores.- 7.4 Jackknife.- 7.5 Model-based method.- 7.6 Examples.- 7.7 Estimating proportions.- 7.8 Regression with survey data.- 7.9 Estimating many subpopulation means.- 7.10 Jackknife and model-based estimators.- 7.11 Summary.- 8 Small-area estimation.- 8.1 Introduction.- 8.2 Shrinkage estimation.- 8.3 Regression with survey data.- 8.4 Fitting two-level regression.- 8.5 Small-area mean prediction.- 8.6 Selection of covariates.- 8.7 Application.- 8.8 Summary and literature review.- 9 Cut scores forpass/fail decisions.- 9.1 Introduction.- 9.2 Models.- 9.3 Fitting logistic regression.- 9.4 Examples.- 9.5 Summary.- 10 Incomplete longitudinal data.- 10.1 Introduction.- 10.2 Informative missingness.- 10.3 Longitudinal analysis.- 10.4 EM algorithm.- 10.5 Application.- 10.6 Estimation.- 10.7 Summary.- References.

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