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The Elements of Mental Tests provides an introduction to mental testing and the use of psychological and educational measures. Part I: The Elements of Measurement introduces the types of educational and psychological tests commonly in use, the test data those measures collect, and the types of test items that make up a test. Part II: The Elements of Test Scores introduces the mathematical models that professionals use to represent test-takers' answers to test questions. Part II begins with a review of basic statistics particularly relevant to measurement, including the conversion of test scores to z-scores and the use of correlation coefficients to relate test items and tests to one another. Part II continues with an integrated introduction to both Classical Test Theory and Item Response Theory-- the most influential methods for understanding tests in use today. Part III: The Elements of Test Quality, examines the standards of good testing including a test's reliability and its precision of measurement, the evaluation of test validity, and the features of a good test administration. Altogether, the book provides a comprehensive foundation for readers who are interested in tests, in testing, and in the use of tests in contemporary life.

Educational tests and measurements. --- Psychological tests. --- Mental tests --- Psychological assessment --- Tests, Psychological --- Psychology --- Testing --- Clinical psychology --- Educational tests and measurements --- Educational assessment --- Educational measurements --- Tests and measurements in education --- Psychological tests for children --- Psychometrics --- Students --- Examinations --- Psychological tests --- Methodology --- Rating of --- Classical Test Theory --- Item Response Theory --- Mental Tests --- Psychological Tests

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In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series of Raven’s (1941) Standard Progressive Matrices. Although the original paper already proposed several modeling strategies, this issue presents new or improved procedures to study the psychometrics properties of tests of this type.

Psychology --- Raven matrices --- Standard Progressive Matrices test --- dimensionality --- bi-factor --- parallel analysis --- target rotation --- exploratory graph analysis --- E-assessment --- general mental ability --- nested logit models --- item-response theory --- ability-based guessing --- Standard Progressive Matrices --- Item Response Theory --- Bayesian statistics --- brms --- Stan --- R --- Raven’s progressive matrices --- intelligence --- distractors --- item analysis --- intelligence tests --- classical test theory --- IRT --- interaction model --- test-item regression --- Mokken scale analysis --- non-parametric item response theory --- psychometrics --- invariant item ordering --- regularized latent class analysis --- regularization --- fused regularization --- fused grouped regularization --- distractor analysis --- n/a --- Raven's progressive matrices

Choose an application

• Reference Manager
• EndNote
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In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series of Raven’s (1941) Standard Progressive Matrices. Although the original paper already proposed several modeling strategies, this issue presents new or improved procedures to study the psychometrics properties of tests of this type.

Psychology --- Raven matrices --- Standard Progressive Matrices test --- dimensionality --- bi-factor --- parallel analysis --- target rotation --- exploratory graph analysis --- E-assessment --- general mental ability --- nested logit models --- item-response theory --- ability-based guessing --- Standard Progressive Matrices --- Item Response Theory --- Bayesian statistics --- brms --- Stan --- R --- Raven's progressive matrices --- intelligence --- distractors --- item analysis --- intelligence tests --- classical test theory --- IRT --- interaction model --- test-item regression --- Mokken scale analysis --- non-parametric item response theory --- psychometrics --- invariant item ordering --- regularized latent class analysis --- regularization --- fused regularization --- fused grouped regularization --- distractor analysis --- Raven matrices --- Standard Progressive Matrices test --- dimensionality --- bi-factor --- parallel analysis --- target rotation --- exploratory graph analysis --- E-assessment --- general mental ability --- nested logit models --- item-response theory --- ability-based guessing --- Standard Progressive Matrices --- Item Response Theory --- Bayesian statistics --- brms --- Stan --- R --- Raven's progressive matrices --- intelligence --- distractors --- item analysis --- intelligence tests --- classical test theory --- IRT --- interaction model --- test-item regression --- Mokken scale analysis --- non-parametric item response theory --- psychometrics --- invariant item ordering --- regularized latent class analysis --- regularization --- fused regularization --- fused grouped regularization --- distractor analysis