Computational Aspects of Psychometric Methods. With R

Book cover
This book covers the computational aspects of psychometric methods involved in developing measurement instruments and analyzing measurement data in social sciences. It covers the main topics of psychometrics such as validity, reliability, item analysis, item response theory models, and computerized adaptive testing. The computational aspects comprise the statistical theory and models, comparison of estimation methods and algorithms, as well as an implementation with practical data examples in R and also in an interactive ShinyItemAnalysis application. Key Features:
  • Statistical models and estimation methods involved in psychometric research
  • Includes reproducible R code and examples with real datasets
  • Interactive implementation in ShinyItemAnalysis application
The book is targeted toward a wide range of researchers in the field of educational, psychological, and health-related measurements. It is also intended for those developing measurement instruments and for those collecting and analyzing data from behavioral measurements, who are searching for a deeper understanding of underlying models and further development of their analytical skills.


First edition

Page 98: model1 <- lmer(Score ~ 1 + (1|ID), data = AIBS, REML = TRUE))
should be: model1_REML <- lmer(Score ~ 1 + (1|ID), data = AIBS, REML = TRUE)

Page 107: (G_pxi <- hemp::gstudy(fit_2wayr))
should be: (G_pxi <- hemp::gstudy(model2_REML))

Page 180: fit_rasch_TAM2 <- tam.mml(resp = HCI[, 1:20], model = "Rasch")
should be: fit_rasch_TAM2 <- tam.mml(resp = HCI[, 1:20], irtmodel = "Rasch")

Thanks to Chen Jiexin.

Additional materials

R code and datasets

Hints for exercises (TBA)

Slides (TBA)

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