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Lim, Euijin; Lee, Won-Chan – Applied Measurement in Education, 2020
The purpose of this study is to address the necessity of subscore equating and to evaluate the performance of various equating methods for subtests. Assuming the random groups design and number-correct scoring, this paper analyzed real data and simulated data with four study factors including test dimensionality, subtest length, form difference in…
Descriptors: Equated Scores, Test Length, Test Format, Difficulty Level
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Sunbul, Onder; Yormaz, Seha – International Journal of Evaluation and Research in Education, 2018
In this study Type I Error and the power rates of omega (?) and GBT (generalized binomial test) indices were investigated for several nominal alpha levels and for 40 and 80-item test lengths with 10,000-examinee sample size under several test level restrictions. As a result, Type I error rates of both indices were found to be below the acceptable…
Descriptors: Difficulty Level, Cheating, Duplication, Test Length
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Svetina, Dubravka; Levy, Roy – Journal of Experimental Education, 2016
This study investigated the effect of complex structure on dimensionality assessment in compensatory multidimensional item response models using DETECT- and NOHARM-based methods. The performance was evaluated via the accuracy of identifying the correct number of dimensions and the ability to accurately recover item groupings using a simple…
Descriptors: Item Response Theory, Accuracy, Correlation, Sample Size
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Socha, Alan; DeMars, Christine E. – Educational and Psychological Measurement, 2013
Modeling multidimensional test data with a unidimensional model can result in serious statistical errors, such as bias in item parameter estimates. Many methods exist for assessing the dimensionality of a test. The current study focused on DIMTEST. Using simulated data, the effects of sample size splitting for use with the ATFIND procedure for…
Descriptors: Sample Size, Test Length, Correlation, Test Format
Harris, Dickie A.; Penell, Roger J. – 1977
This study used a series of simulations to answer questions about the efficacy of adaptive testing raised by empirical studies. The first study showed that for reasonable high entry points, parameters estimated from paper-and-pencil test protocols cross-validated remarkably well to groups actually tested at a computer terminal. This suggested that…
Descriptors: Adaptive Testing, Computer Assisted Testing, Cost Effectiveness, Difficulty Level
Scheetz, James P.; Forsyth, Robert A. – 1977
Empirical evidence is presented related to the effects of using a stratified sampling of items in multiple matrix sampling on the accuracy of estimates of the population mean. Data were obtained from a sample of 600 high school students for a 36-item mathematics test and a 40-item vocabulary test, both subtests of the Iowa Tests of Educational…
Descriptors: Achievement Tests, Difficulty Level, Item Analysis, Item Sampling
de Jong, John H. A. L. – 1984
The Netherlands' secondary education system is highly differentiated, with four different school types for four scholastic ability levels. Final examinations must accommodate these four levels, and require a test-independent definition of the intended final ability levels as well as a sample-free evaluation of the range of ability levels at which…
Descriptors: Difficulty Level, Efficiency, Equated Scores, Foreign Countries
Cliff, Norman; And Others – 1977
TAILOR is a computer program that uses the implied orders concept as the basis for computerized adaptive testing. The basic characteristics of TAILOR, which does not involve pretesting, are reviewed here and two studies of it are reported. One is a Monte Carlo simulation based on the four-parameter Birnbaum model and the other uses a matrix of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Programs, Difficulty Level