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Lee, Chansoon; Qian, Hong – Educational and Psychological Measurement, 2022
Using classical test theory and item response theory, this study applied sequential procedures to a real operational item pool in a variable-length computerized adaptive testing (CAT) to detect items whose security may be compromised. Moreover, this study proposed a hybrid threshold approach to improve the detection power of the sequential…
Descriptors: Computer Assisted Testing, Adaptive Testing, Licensing Examinations (Professions), Item Response Theory
Wind, Stefanie A. – Educational and Psychological Measurement, 2023
Rating scale analysis techniques provide researchers with practical tools for examining the degree to which ordinal rating scales (e.g., Likert-type scales or performance assessment rating scales) function in psychometrically useful ways. When rating scales function as expected, researchers can interpret ratings in the intended direction (i.e.,…
Descriptors: Rating Scales, Testing Problems, Item Response Theory, Models
Sinharay, Sandip – Educational and Psychological Measurement, 2022
Administrative problems such as computer malfunction and power outage occasionally lead to missing item scores and hence to incomplete data on mastery tests such as the AP and U.S. Medical Licensing examinations. Investigators are often interested in estimating the probabilities of passing of the examinees with incomplete data on mastery tests.…
Descriptors: Mastery Tests, Computer Assisted Testing, Probability, Test Wiseness
Schweizer, Karl; Reiß, Siegbert; Troche, Stefan – Educational and Psychological Measurement, 2019
The article reports three simulation studies conducted to find out whether the effect of a time limit for testing impairs model fit in investigations of structural validity, whether the representation of the assumed source of the effect prevents impairment of model fit and whether it is possible to identify and discriminate this method effect from…
Descriptors: Timed Tests, Testing, Barriers, Testing Problems
von Davier, Matthias; Bezirhan, Ummugul – Educational and Psychological Measurement, 2023
Viable methods for the identification of item misfit or Differential Item Functioning (DIF) are central to scale construction and sound measurement. Many approaches rely on the derivation of a limiting distribution under the assumption that a certain model fits the data perfectly. Typical DIF assumptions such as the monotonicity and population…
Descriptors: Robustness (Statistics), Test Items, Item Analysis, Goodness of Fit
Miller, Jeff – Educational and Psychological Measurement, 2017
Critics of null hypothesis significance testing suggest that (a) its basic logic is invalid and (b) it addresses a question that is of no interest. In contrast to (a), I argue that the underlying logic of hypothesis testing is actually extremely straightforward and compelling. To substantiate that, I present examples showing that hypothesis…
Descriptors: Hypothesis Testing, Testing Problems, Test Validity, Relevance (Education)
Sinharay, Sandip; Johnson, Matthew S. – Educational and Psychological Measurement, 2017
In a pioneering research article, Wollack and colleagues suggested the "erasure detection index" (EDI) to detect test tampering. The EDI can be used with or without a continuity correction and is assumed to follow the standard normal distribution under the null hypothesis of no test tampering. When used without a continuity correction,…
Descriptors: Deception, Identification, Testing Problems, Error of Measurement
Robitzsch, Alexander; Rupp, Andre A. – Educational and Psychological Measurement, 2009
This article describes the results of a simulation study to investigate the impact of missing data on the detection of differential item functioning (DIF). Specifically, it investigates how four methods for dealing with missing data (listwise deletion, zero imputation, two-way imputation, response function imputation) interact with two methods of…
Descriptors: Test Bias, Simulation, Interaction, Effect Size

Roos, Linda L.; And Others – Educational and Psychological Measurement, 1996
This article describes Minnesota Computerized Adaptive Testing Language program code for using the MicroCAT 3.5 testing software to administer several types of self-adapted tests. Code is provided for: a basic self-adapted test; a self-adapted version of an adaptive mastery test; and a restricted self-adapted test. (Author/SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Mastery Tests, Programming

Schmidt, Frank L.; And Others – Educational and Psychological Measurement, 1978
Computer assisted tailored testing was used in a study of 163 Civil Service examinees to assess examinee's affective response to the testing setting. Response was summarized as overwhelmingly positive. (Author/JKS)
Descriptors: Adaptive Testing, Adults, Attitudes, Computer Assisted Testing

Bird, Kevin D. – Educational and Psychological Measurement, 1991
A method is outlined for analysis of the shape of an individual profile of scores on a standardized test battery. The method uses a simultaneous test procedure allowing for an overall test of profile flatness, with follow-up tests on all contrasts of interest. (SLD)
Descriptors: Equations (Mathematics), Hypothesis Testing, Mathematical Models, Profiles

Krus, David J.; Ceurvorst, Robert W. – Educational and Psychological Measurement, 1978
An algorithm for updating the means of variances of a norm group after each computer-assisted administration of a test is described. The algorithm does not require storage of the whole data set, and provides for unlimited, continuous expansion of the test norms. (Author)
Descriptors: Computer Assisted Testing, Computer Programs, Norms, Statistical Data

Keselman, H. J.; And Others – Educational and Psychological Measurement, 1981
This paper demonstrates that multiple comparison tests using a pooled error term are dependent on the circularity assumption and shows how to compute tests which are insensitive (robust) to this assumption. (Author/GK)
Descriptors: Hypothesis Testing, Mathematical Models, Research Design, Statistical Significance

Endler, Norman S.; Parker, James D. A. – Educational and Psychological Measurement, 1990
C. Davis and M. Cowles (1989) analyzed a total trait anxiety score on the Endler Multidimensional Anxiety Scales (EMAS)--a unidimensional construct that this multidimensional measure does not assess. Data are reanalyzed using the appropriate scoring procedure for the EMAS. Subjects included 145 undergraduates in 1 of 4 testing conditions. (SLD)
Descriptors: Anxiety, Comparative Testing, Computer Assisted Testing, Construct Validity

Boldt, R. F. – Educational and Psychological Measurement, 1974
Descriptors: Comparative Testing, Equated Scores, National Norms, Raw Scores