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Aybek, Eren Can; Demirtasli, R. Nukhet – International Journal of Research in Education and Science, 2017
This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
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Green, Bert F. – 2002
Maximum likelihood and Bayesian estimates of proficiency, typically used in adaptive testing, use item weights that depend on test taker proficiency to estimate test taker proficiency. In this study, several methods were explored through computer simulation using fixed item weights, which depend mainly on the items difficulty. The simpler scores…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Computer Simulation
Zeng, Lingjia; Bashaw, Wilbur L. – 1990
A joint maximum likelihood estimation algorithm, based on the partial compensatory multidimensional logistic model (PCML) proposed by L. Zeng (1989), is presented. The algorithm simultaneously estimates item difficulty parameters, the strength of each dimension, and individuals' abilities on each of the dimensions involved in arriving at a correct…
Descriptors: Ability Identification, Algorithms, Computer Simulation, Difficulty Level
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Samejima, Fumiko – Psychometrika, 1994
Using the constant information model, constant amounts of test information, and a finite interval of ability, simulated data were produced for 8 ability levels and 20 numbers of test items. Analyses suggest that it is desirable to consider modifying test information functions when they measure accuracy in ability estimation. (SLD)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Computer Simulation
Kim, Seock-Ho; Cohen, Allan S. – 1997
Type I error rates of the likelihood ratio test for the detection of differential item functioning (DIF) were investigated using Monte Carlo simulations. The graded response model with five ordered categories was used to generate data sets of a 30-item test for samples of 300 and 1,000 simulated examinees. All DIF comparisons were simulated by…
Descriptors: Ability, Classification, Computer Simulation, Estimation (Mathematics)
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Seong, Tae-Je – Applied Psychological Measurement, 1990
The sensitivity of marginal maximum likelihood estimation of item and ability (theta) parameters was examined when prior ability distributions were not matched to underlying ability distributions. Thirty sets of 45-item test data were generated. Conditions affecting the accuracy of estimation are discussed. (SLD)
Descriptors: Ability, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
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Liou, Michelle; Chang, Chih-Hsin – Psychometrika, 1992
An extension is proposed for the network algorithm introduced by C.R. Mehta and N.R. Patel to construct exact tail probabilities for testing the general hypothesis that item responses are distributed according to the Rasch model. A simulation study indicates the efficiency of the algorithm. (SLD)
Descriptors: Algorithms, Computer Simulation, Difficulty Level, Equations (Mathematics)
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Rost, Jurgen – Applied Psychological Measurement, 1990
Combining Rasch and latent class models is presented as a way to overcome deficiencies and retain the positive features of both. An estimation algorithm is outlined, providing conditional maximum likelihood estimates of item parameters for each class. The model is illustrated with simulated data and real data (n=869 adults). (SLD)
Descriptors: Adults, Algorithms, Computer Simulation, Equations (Mathematics)
Samejima, Fumiko – 1984
In order to evaluate our methods and approaches of estimating the operating characteristics of discrete item responses, it is necessary to try other comparable methods on similar sets of data. LOGIST 5 was taken up for this reason, and was tried upon the hypothetical test items, which follow the normal ogive model and were used frequently in…
Descriptors: Computer Simulation, Computer Software, Estimation (Mathematics), Item Analysis
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Dodd, Barbara G. – Applied Psychological Measurement, 1990
Using one simulated and two real data sets, the effects of the systematic variation of the item-selection procedure and the stepsize method on the operating characteristics of computerized adaptive testing (CAT) for instruments with polychotomously scored rating scale items were studied. The six rating scale CAT procedures used performed well.…
Descriptors: Adaptive Testing, Attitude Measures, Comparative Analysis, Computer Assisted Testing
Drasgow, Fritz; Parsons, Charles K. – 1982
The effects of a multidimensional latent trait space on estimation of item and person parameters by the computer program LOGIST are examined. Several item pools were simulated that ranged from truly unidimensional to an inconsequential general latent trait. Item pools with intermediate levels of prepotency of the general latent trait were also…
Descriptors: Computer Simulation, Computer Software, Difficulty Level, Item Analysis
Mislevy, Robert J.; Bock, R. Darrell – 1982
This paper reviews the basic elements of the EM approach to estimating item parameters and illustrates its use with one simulated and one real data set. In order to illustrate the use of the BILOG computer program, runs for 1-, 2-, and 3-parameter models are presented for the two sets of data. First is a set of responses from 1,000 persons to five…
Descriptors: College Entrance Examinations, Computer Oriented Programs, Computer Simulation, Computer Software
Carlson, James E. – 1993
In this article some results are presented relating to the dimensionality of instruments containing polytomously scored as well as dichotomously scored items, concentrating on the 1992 National Assessment of Educational Progress' (NAEP) mathematics and reading assessment data and several simulated datasets. The maximum likelihood factor analytic…
Descriptors: Computer Simulation, Correlation, Elementary Secondary Education, Factor Analysis