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Peer reviewedBarcikowski, Robert S. – Journal of Educational Measurement, 1972
These results indicate that in deciding on the data-gathering design to be used in seeking norm information, attention should be given to item characteristics and test length with particular attention paid to the range of biserial correlations between item response and ability. (Author)
Descriptors: Item Sampling, Mathematical Models, Measurement Techniques, Monte Carlo Methods
Peer reviewedDavison, Mark L., Ed.; Jones, Lawrence E., Ed. – Applied Psychological Measurement, 1983
This special issues describes multidimensional scaling (MDS), with emphasis on proximity and preference models. An introduction and six papers review statistical developments in MDS study design and scrutinize MDS research in four areas of application (consumer, social, cognitive, and vocational psychology). (SLD)
Descriptors: Cognitive Psychology, Mathematical Models, Monte Carlo Methods, Multidimensional Scaling
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
Direct linkStark, Stephen; Chernyshenko, Oleksandr S.; Drasgow, Fritz – Applied Psychological Measurement, 2005
This article proposes an item response theory (IRT) approach to constructing and scoring multidimensional pairwise preference items. Individual statements are administered and calibrated using a unidimensional single-stimulus model. Tests are created by combining multidimensional items with a small number of unidimensional pairings needed to…
Descriptors: Test Construction, Scoring, Mathematical Models, Item Response Theory
Peer reviewedSchiel, Jeffrey L.; Shaw, Dale G. – Applied Measurement in Education, 1992
Changes in information retention resulting from changes in reliability and number of intervals in scale construction were studied to provide quantitative information to help in decisions about choosing intervals. Information retention reached a maximum when the number of intervals was about 8 or more and reliability was near 1.0. (SLD)
Descriptors: Decision Making, Knowledge Level, Mathematical Models, Monte Carlo Methods
Download full textKromrey, Jeffrey D.; Bacon, Tina P. – 1992
A Monte Carlo study was conducted to estimate the small sample standard errors and statistical bias of psychometric statistics commonly used in the analysis of achievement tests. The statistics examined in this research were: (1) the index of item difficulty; (2) the index of item discrimination; (3) the corrected item-total point-biserial…
Descriptors: Achievement Tests, Comparative Analysis, Difficulty Level, Estimation (Mathematics)
Peer reviewedAckerman, Terry A. – Journal of Educational Measurement, 1992
The difference between item bias and item impact and the way they relate to item validity are discussed from a multidimensional item response theory perspective. The Mantel-Haenszel procedure and the Simultaneous Item Bias strategy are used in a Monte Carlo study to illustrate detection of item bias. (SLD)
Descriptors: Causal Models, Computer Simulation, Construct Validity, Equations (Mathematics)
Kirisci, Levent; Hsu, Tse-Chi – 1992
A predictive adaptive testing (PAT) strategy was developed based on statistical predictive analysis, and its feasibility was studied by comparing PAT performance to those of the Flexilevel, Bayesian modal, and expected a posteriori (EAP) strategies in a simulated environment. The proposed adaptive test is based on the idea of using item difficulty…
Descriptors: Adaptive Testing, Bayesian Statistics, Comparative Analysis, Computer Assisted Testing
Xiao, Beiling – 1990
Dichotomous search strategies (DSSs) for computerized adaptive testing are similar to golden section search strategies (GSSSs). Each middle point of successive search regions is a testing point. After each item is administered, the subject's obtained score is compared with the expected score at successive testing points. If the subject's obtained…
Descriptors: Ability Identification, Adaptive Testing, Computer Assisted Testing, Equations (Mathematics)
Patience, Wayne M.; Reckase, Mark D. – 1979
An experiment was performed with computer-generated data to investigate some of the operational characteristics of tailored testing as they are related to various provisions of the computer program and item pool. With respect to the computer program, two characteristics were varied: the size of the step of increase or decrease in item difficulty…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Error of Measurement
