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Berger, Stéphanie; Verschoor, Angela J.; Eggen, Theo J. H. M.; Moser, Urs – Journal of Educational Measurement, 2019
Calibration of an item bank for computer adaptive testing requires substantial resources. In this study, we investigated whether the efficiency of calibration under the Rasch model could be enhanced by improving the match between item difficulty and student ability. We introduced targeted multistage calibration designs, a design type that…
Descriptors: Simulation, Computer Assisted Testing, Test Items, Difficulty Level
Svetina, Dubravka; Liaw, Yuan-Ling; Rutkowski, Leslie; Rutkowski, David – Journal of Educational Measurement, 2019
This study investigates the effect of several design and administration choices on item exposure and person/item parameter recovery under a multistage test (MST) design. In a simulation study, we examine whether number-correct (NC) or item response theory (IRT) methods are differentially effective at routing students to the correct next stage(s)…
Descriptors: Measurement, Item Analysis, Test Construction, Item Response Theory
Joo, Seang-Hwane; Lee, Philseok; Stark, Stephen – Journal of Educational Measurement, 2018
This research derived information functions and proposed new scalar information indices to examine the quality of multidimensional forced choice (MFC) items based on the RANK model. We also explored how GGUM-RANK information, latent trait recovery, and reliability varied across three MFC formats: pairs (two response alternatives), triplets (three…
Descriptors: Item Response Theory, Models, Item Analysis, Reliability
Albano, Anthony D. – Journal of Educational Measurement, 2013
In many testing programs it is assumed that the context or position in which an item is administered does not have a differential effect on examinee responses to the item. Violations of this assumption may bias item response theory estimates of item and person parameters. This study examines the potentially biasing effects of item position. A…
Descriptors: Test Items, Item Response Theory, Test Format, Questioning Techniques
Kim, Sooyeon; Walker, Michael E.; McHale, Frederick – Journal of Educational Measurement, 2010
In this study we examined variations of the nonequivalent groups equating design for tests containing both multiple-choice (MC) and constructed-response (CR) items to determine which design was most effective in producing equivalent scores across the two tests to be equated. Using data from a large-scale exam, this study investigated the use of…
Descriptors: Measures (Individuals), Scoring, Equated Scores, Test Bias

Menne, John W.; Tolsma, Robert J. – Journal of Educational Measurement, 1971
Descriptors: Discriminant Analysis, Group Testing, Item Analysis, Psychometrics

Woodson, M. I. Chas. E. – Journal of Educational Measurement, 1974
Descriptors: Criterion Referenced Tests, Item Analysis, Test Construction, Test Reliability

Faggen-Steckler, Jane; And Others – Journal of Educational Measurement, 1974
Descriptors: Item Analysis, Sex Discrimination, Sex Stereotypes, Standardized Tests

Wainer, Howard – Journal of Educational Measurement, 1989
This paper reviews the role of the item in test construction, and suggests some new methods of item analysis. A look at dynamic, graphical item analysis is provided that uses the advantages of modern, high-speed, highly interactive computing. Several illustrations are provided. (Author/TJH)
Descriptors: Computer Assisted Testing, Computer Graphics, Graphs, Item Analysis

Whitely, Susan E.; Dawis, Rene V. – Journal of Educational Measurement, 1974
Descriptors: Error of Measurement, Item Analysis, Matrices, Measurement Techniques

Haladyna, Thomas Michael – Journal of Educational Measurement, 1974
Classical test construction and analysis procedures are applicable and appropriate for use with criterion referenced tests when samples of both mastery and nonmastery examinees are employed. (Author/BB)
Descriptors: Criterion Referenced Tests, Item Analysis, Mastery Tests, Test Construction

Woodson, M. I. Charles E. – Journal of Educational Measurement, 1974
The basis for selection of the calibration sample determines the kind of scale which will be developed. A random sample from a population of individuals leads to a norm-referenced scale, and a sample representative of abilities of a range of characteristics leads to a criterion-referenced scale. (Author/BB)
Descriptors: Criterion Referenced Tests, Discriminant Analysis, Item Analysis, Test Construction

Reckase, Mark D.; And Others – Journal of Educational Measurement, 1988
It is demonstrated, theoretically and empirically, that item sets can be selected that meet the unidimensionality assumption of most item response theory models, even though they require more than one ability for a correct response. A method for identifying such item sets for test development purposes is presented. (SLD)
Descriptors: Computer Simulation, Item Analysis, Latent Trait Theory, Mathematical Models

Schwartz, Steven A. – Journal of Educational Measurement, 1978
A method for the construction of scales which combines the rational (or intuitive) approach with an empirical (item analysis) approach is presented. A step-by-step procedure is provided. (Author/JKS)
Descriptors: Factor Analysis, Item Analysis, Measurement, Psychological Testing

Terwilliger, James S.; Lele, Kaustubh – Journal of Educational Measurement, 1979
Different indices for the internal consistency, reproducibility, or homogeneity of a test are based upon highly similar conceptual frameworks. Illustrations are presented to demonstrate how the maximum and minimum values of KR20 are influenced by test difficulty and the shape of the distribution of test scores. (Author/CTM)
Descriptors: Difficulty Level, Item Analysis, Mathematical Formulas, Statistical Analysis