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Peer reviewedStark, Stephen; Drasgow, Fritz – Applied Psychological Measurement, 2002
Describes item response and information functions for the Zinnes and Griggs paired comparison item response theory (IRT) model (1974) and presents procedures for estimating stimulus and person parameters. Monte Carlo simulations show that at least 400 ratings are required to obtain reasonably accurate estimates of the stimulus parameters and their…
Descriptors: Comparative Analysis, Computer Simulation, Error of Measurement, Item Response Theory
Peer reviewedReise, Steven P.; Due, Allan M. – Applied Psychological Measurement, 1991
Previous person-fit research is extended through explication of an unexplored model for generating aberrant response patterns. The proposed model is then implemented to investigate the influence of test properties on the aberrancy detection power of a person-fit statistic. Difficulties of aberrancy detection are discussed. (SLD)
Descriptors: Algorithms, Computer Simulation, Item Response Theory, Mathematical Models
Download full textAnkenmann, Robert D.; Stone, Clement A. – 1992
Effects of test length, sample size, and assumed ability distribution were investigated in a multiple replication Monte Carlo study under the 1-parameter (1P) and 2-parameter (2P) logistic graded model with five score levels. Accuracy and variability of item parameter and ability estimates were examined. Monte Carlo methods were used to evaluate…
Descriptors: Computer Simulation, Estimation (Mathematics), Item Bias, Mathematical Models
Kim, Haeok; Plake, Barbara S. – 1993
A two-stage testing strategy is one method of adapting the difficulty of a test to an individual's ability level in an effort to achieve more precise measurement. A routing test provides an initial estimate of ability level, and a second-stage measurement test then evaluates the examinee further. The measurement accuracy and efficiency of item…
Descriptors: Ability, Adaptive Testing, Comparative Testing, Computer Assisted Testing
Peer reviewedDonoghue, John R.; Allen, Nancy L. – Journal of Educational Statistics, 1993
Forming the matching variable for the Mantel-Haenszel differential item functioning (DIF) procedure through use of the total score as the matching variable (thin) and forming the matching variable by pooling total score levels (thick) were compared in a Monte Carlo study. Reasons thick matching is superior are discussed. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Graphs
Samejima, Fumiko – 1986
Item analysis data fitting the normal ogive model were simulated in order to investigate the problems encountered when applying the three-parameter logistic model. Binary item tests containing 10 and 35 items were created, and Monte Carlo methods simulated the responses of 2,000 and 500 examinees. Item parameters were obtained using Logist 5.…
Descriptors: Computer Simulation, Difficulty Level, Guessing (Tests), Item Analysis
