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New Horizons in Testing: Latent Trait Test Theory and Computerized Adaptive Testing provides an in-depth analysis of psychological measurement, espoused by the computer-latent trait test theory (item response theory) and computerized adaptive testing.
The book is organized into five parts. The first part addresses basic problems in estimating the parameters of the item response theory models that constitute a class of latent trait test theory models. The second part, discusses the implications of item response theory for measuring individuals using more than just simply a trait level (e.g., ability) score. Part III describes the application of item response theory models to specific applied problems, including the problem of equating tests or linking items into a pool, a latent trait model for timed tests, and the problem of measuring growth using scores derived from the application of item response theory models. Part IV is concerned with the application of item response theory to computerized adaptive testing. Finally, Part V includes discussion of two special models beyond the standard models used in the rest of the book. One of these models, the constant information model, is a simplification of the general latent trait models, whereas the other is an extension of latent trait models to the problem of measuring change.
Psychometricians, psychologists, and psychiatrists will find the book useful.
Latent Trait Theory
I Estimating Item Parameters and Ability
1 Estimation of Parameters in the Three-Parameter Latent Trait Model
Design of the Study
2 Robustness of Item Response Models and Effects of Test Length and Sample Size on the Precision of Ability Estimates
3 Small N Justifies Rasch Model
Appendix: Asymptotic Sampling Variance of ξ
4 Are We Correcting for Guessing in the Wrong Direction?
The Start of an Alternative
A More Specific Plan
An AMJACK Example
II Beyond the Ability Estimate
5 The Person Response Curve: Fit of Individuals to Item Response Theory Models
The Person Response Curve
Conclusions and Directions for Future Research
6 Appropriateness Measurement: Validating Studies and Variable Ability Models
Objectives and Limitations of Appropriateness Measurement
Review of Test Theories and Basic Appropriateness Measurement
Simulation Procedures and Earlier Results
Summary and Concluding Remarks
III Applications to Testing Problems
7 Effects of Sample Size on Linear Equating of Item Characterisfic Curve Parameters
Item Characteristic Curve Parameters
8 A Test of the Adequacy of Curvilinear Score Equating Models
Results and Discussion
9 Timed Testing: An Approach Using Item Response Theory
Applications: I. Spatial Test Data
Applications: II. Three Tests
10 The Mental Growth Curve Reexamined
A Scaling Procedure Fully Independent of Chronological Age Units
Scaling the Binet Test
Advantages of the Present Scaling Procedure
IV Application to Adaptive Testing
11 Reliability and Validity of Adaptive Ability Tests in a Military Setting
Background and Purpose
12 A Procedure for Decision Making Using Tailored Testing
Tailored Testing Procedures
Sequential Decision Procedures
The Sequential Probability Ratio Test
Summary and Conclusions
13 A Comparison of IRT-Based Adaptive Mastery Testing and a Sequential Mastery Testing Procedure
Alternatives to Conventional Mastery Tests
Discussion and Conclusions
V Models for Special Applications
14 The Constant Information Model on the Dichotomous Response Level
The Constant Information Model
Use of the Constant Information Model in the Estimation of the Operating Characteristics of Item Response Categories
Discussion and Conclusion
15 Some Latent Trait Models for Measuring Change in Qualitative Observations
A Family of Linear Logistic Models for Qualitative Data
The Dichotomous Linear Logistic Model with Relaxed Assumptions
The Epistemological Background of the Linear Logistic Model with Relaxed Assumptions
Estimating Model Parameters in the Linear Logistic Model with Relaxed Assumptions
Testing Hypotheses with the Linear Logistic Model with Relaxed Assumptions
The Polytomous Linear Logistic Model with Relaxed Assumptions
- No. of pages:
- © Academic Press 1983
- 28th October 1983
- Academic Press
- eBook ISBN:
University of Minnesota, Minneapolis, U.S.A.
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