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Peer reviewedWilcox, Rand R. – Journal of Educational Measurement, 1982
A new model for measuring misinformation is suggested. A modification of Wilcox's strong true-score model, to be used in certain situations, is indicated, since it solves the problem of correcting for guessing without assuming guessing is random. (Author/GK)
Descriptors: Achievement Tests, Guessing (Tests), Mathematical Models, Scoring Formulas
Peer reviewedWilcox, Rand R. – Educational and Psychological Measurement, 1980
Technical problems in achievement testing associated with using latent structure models to estimate the probability of guessing correct responses by examinees is studied; also the lack of problems associated with using Wilcox's formula score. Maximum likelihood estimates are derived which may be applied when items are hierarchically related.…
Descriptors: Guessing (Tests), Item Analysis, Mathematical Models, Maximum Likelihood Statistics
Peer reviewedDrasgow, Fritz; And Others – Applied Psychological Measurement, 1989
Multilinear formula scoring (MFS) is reviewed, with emphasis on estimating option characteristic curves (OCSs). MFS was used to estimate OCSs for the arithmetic reasoning subtest of the Armed Services Vocational Aptitude Battery for 2,978 examinees. A second analysis obtained OCSs for simulated data. The use of MFS is discussed. (SLD)
Descriptors: Estimation (Mathematics), Mathematical Models, Multiple Choice Tests, Scores
Peer reviewedGarcia-Perez, Miguel A.; Frary, Robert B. – Applied Psychological Measurement, 1989
Simulation techniques were used to generate conventional test responses and track the proportion of alternatives examinees could classify independently before and after taking the test. Finite-state scores were compared with these actual values and with number-correct and formula scores. Finite-state scores proved useful. (TJH)
Descriptors: Comparative Analysis, Computer Simulation, Guessing (Tests), Mathematical Models
Peer reviewedMcGaw, Barry; Glass, Gene V. – American Educational Research Journal, 1980
There are difficulties in expressing effect sizes on a common metric when some studies use transformed scales to express group differences, or use factorial designs or covariance adjustments to obtain a reduced error term. A common metric on which effect sizes may be standardized is described. (Author/RL)
Descriptors: Control Groups, Error of Measurement, Mathematical Models, Research Problems
Peer reviewedPenfield, Douglas A.; Koffler, Stephen L. – Journal of Experimental Education, 1978
Three nonparametric alternatives to the parametric Bartlett test are presented for handling the K-sample equality of variance problem. The two-sample Siegel-Tukey test, Mood test, and Klotz test are extended to the multisample situation by Puri's methods. These K-sample scale tests are illustrated and compared. (Author/GDC)
Descriptors: Comparative Analysis, Guessing (Tests), Higher Education, Mathematical Models
van der Linden, Wim J. – Evaluation in Education: International Progress, 1982
In mastery testing a linear relationship between an optimal passing score and test length is presented with a new optimization criterion. The usual indifference zone approach, a binomial error model, decision errors, and corrections for guessing are discussed. Related results in sequential testing and the latent class approach are included. (CM)
Descriptors: Cutting Scores, Educational Testing, Mastery Tests, Mathematical Models


