Computerized Adaptive Testing in Kinanthropology : Monte Carlo Simulations Using the Physical Self-Description Questionnaire.
- 1st ed.
- 1 online resource (132 pages)
Cover -- Contents -- Acknowledgements -- 1. Brief introductionto measurement(in Kinanthropology) -- 2. Historical Pathsto Modern Test Theory -- 3. Groundwork forItem Response Theory -- 4. Item Response Theory (IRT) -- 4.1 Introduction -- 4.2 Unidimensional dichotomous IRT models -- 4.3 Unidimensional polytomous IRT models -- 4.4 Assumptions required for unidimensional IRT models -- 4.5 Parameter estimation in IRT models -- 4.5.1 Latent trait (θ) estimation -- 4.5.2 Item parameters estimation -- 4.6 Information and standard error of the θ estimates -- 5. Computerized AdaptiveTesting (CAT): Historicaland conceptual origins -- 6. Testing algorithmsin unidimensionalIRT-based CAT -- 6.1 Starting -- 6.2 Continuing -- 6.3 Stopping -- 6.4 Practical issues related to item selection in CAT -- 6.4.1 Item pool -- 6.4.2 Content balancing -- 6.4.3 Exposure control -- 6.5 Evaluation of item selection and trait estimation methodsused in computerized adaptive testing algorithms -- 7. Empirical part -problem statement -- 8. Aims and hypotheses -- 9. Methods -- 9.1 Item pool, IRT model used for item calibration,dimensionality analysis -- 9.1.1 General description of the item pool -- 9.1.2 Item calibration -- 9.1.3 Dimensionality analysis -- 9.2 CAT simulation design and specifications -- 9.2.1 Step 1. Simulate latent trait values (true θ) -- 9.2.2 Step 2. Supply item parameters for the intended item pool -- 9.2.3 Step 3. Set CAT algorithm options -- 9.2.4 Step 4. Simulate CAT administration -- 9.3 Analysis of simulation results -- 10. Results -- 10.1 Dimensionality -- 10.2 Number of administered items in CAT simulation -- 10.3 Bias of the CAT latent trait estimates -- 10.4 Correlations -- 11. Discussion -- 12. Conclusions -- Summary -- References -- Appendices. Appendix A - IRT parameters (a - discrimination and b's -thresholds) for the Physical Self-Description Questionnaireitems (source: Flatcher & -- Hattie, 2004) -- Appendix B - R code used for the simulation of the PSDQ CAT -- Appendix C - Test information and corresponding standarderror for the Physical Self-Description Questionnaireitem pool -- Appendix D - Example of R code used to create Figure 1 -- Appendix E - Online application for adaptive testing usingthe Physical Self-Description Questionnaire -- List of Tables -- List of Figures.