This proceedings volume highlights the latest research and developments in psychometrics and statistics. It represents selected and peer-reviewed presentations given at the 85th Annual International Meeting of the Psychometric Society (IMPS), held virtually on July 13-17, 2020.
The IMPS is one of the largest international meetings on quantitative measurement in education, psychology and the social sciences. It draws approximately 500 participants from around the world, featuring paper and poster presentations, symposiums, workshops, keynotes, and invited presentations.
Leading experts and promising young researchers have written the included chapters. The chapters address a wide variety of topics including but not limited to item response theory, adaptive testing, Bayesian estimation, propensity scores, and cognitive diagnostic models. This volume is the 9th in a series of recent works to cover research presented at the IMPS.
Table of Contents:
Chapter 1. A Rotation Criterion that Encourages a Hierarchical Factor Structure.- Chapter 2. Comparison between different estimation methods of factor models for longitudinal ordinal data.- Chapter 3. An Efficient Scheduling Algorithm for Parallel Planar Rotations of Factors.- Chapter 4. Explanatory Response Time Models.- Chapter 5. Response Time Relationships Within Examinees: Implications for Item Response Time Models.- Chapter 6. Nonlinear Latent Effects in Diagnostic Classification Modeling Incorporating Response Times.- Chapter 7. Sequential Monitoring of Aberrant Test-taking Behaviors Based on Response Times.- Chapter 8. Estimating Approximate Number Sense (ANS) Acuity.- Chapter 9. Differences in Symbolic and Non-Symbolic Measures of Approximate Number Sense.- Chapter 10. Formulas of Multilevel Reliabilities for Tests with Ordered Categorical Responses.- Chapter 11. Polytomous IRT models versus IRTree models for scoring non-cognitive latent traits.- Chapter 12. On the coefficient alpha in high-dimensions.- Chapter 13. IRT Analysis of Dimensional Structure and Item Wording Effects.- Chapter 14. Item Level Measurement of Extreme Response Style.- Chapter 15. On the marginal effect under partitioned populations: Definition and Interpretation.- Chapter 16. Range-preserving confidence intervals and significance tests for scalability coefficients in Mokken scale analysis.- Chapter 17. Equating Nonequivalent Groups using Propensity Scores – Model Misspecification and Sensitivity analysis.- Chapter 18. Possible factors which may impact kernel equating of mixed-format tests.- Chapter 19. Population Invariance of Equating for Subgroups Differing in Achievement Level.- Chapter 20. Comparison of Outlier Detection Methods in NEAT Design.- Chapter 21. An Illustration on the Quantile-Based Calculation of the Standard Error of Equating in Kernel equating.- Chapter 22. Improving Measurement Efficiency of Test Construction in Cognitive Diagnosis Models.- Chapter 23. Exploring Temporal Functional Dependencies between Latent Skills in Cognitive Diagnostic Models.- Chapter 24. Sample size for Latent Dirichlet Allocation of Constructed-Response Items.- Chapter 25. The asymptotic power of the Lagrange Multiplier tests for misspecified IRT models.- Chapter 26. Residual Analysis in Rasch Counts Models.- Chapter 27. A Bayesian solution to non-convergence of crossed random effects models.- Chapter 28. Priors in Bayesian Estimation under the TwoParameter Logistic Model.- Chapter 29. Increasing Measurement Precision of PISA through a Multistage Adaptive Testing.- Chapter 30. Simulation studies of item bias estimation accuracy.- Chapter 31. Multiple answer multiple choice items: A problematic item type?
About the Author :
Marie Wiberg is professor of statistics with a specialty in psychometrics at Umeå University, Sweden. Her research interests include test equating, applied statistics, large-scale assessments and psychometrics in general.
Dylan Molenaar is assistant professor at the department of psychology, University of Amsterdam, the Netherlands. His research interests include item response theory, factor analysis, response time modeling, mixture modeling, modeling of intelligence test data, and modeling of genotype by environmental interactions.
Jorge González is associate professor at the department of statistics, Pontificia Universidad Católica de Chile. His research interests include statistical modeling of social sciences data, particularly in the fields of educational measurement and psychometrics.
Ulf Böckenholt is the John D. Gray Chair in Marketing at the Kellogg School of Management, Northwestern University.He is interested in the development and application of statistical and psychometric methods.
Jee-Seon Kim is professor in the department of educational psychology at the University of Wisconsin-Madison. Her research interests include multilevel and hierarchical modeling, longitudinal data analysis, latent variable modeling, and causal inference with clustered observational data.
