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Ashler, Daniel – Journal of Educational Statistics, 1979
The negative bias of biserial correlations in the presence of guessing is demonstrated by Monte Carlo studies, and another estimator is described that is free of such bias. The usual biserial-correlation assumptions and assumptions about guessing are discussed. Brogden's coefficient of selective efficiency and the triserial correlation are…
Descriptors: Correlation, Guessing (Tests), Item Analysis, Simulation
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Frary, Robert B. – Journal of Educational Statistics, 1982
Six different approaches to scoring test data, including number right, correction for guessing, and answer-until-correct, were investigated using Monte Carlo techniques. Modes permitting multiple response showed higher internal consistency, but there was little difference among modes for a validity measure. (JKS)
Descriptors: Guessing (Tests), Measurement Techniques, Multiple Choice Tests, Scoring Formulas
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van der Linden, Wim J. – Journal of Educational Statistics, 1978
Macready and Dayton introduced two probabilistic models for mastery assessment based on an idealistic all-or-none conception of mastery. Alternatively, an application of latent trait theory to mastery testing is proposed (a three parameter logistic model) as a more plausible model for test theory. (Author/CTM)
Descriptors: Criterion Referenced Tests, Guessing (Tests), Item Analysis, Latent Trait Theory
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Levine, Michael V.; Rubin, Donald B. – Journal of Educational Statistics, 1979
A student may be so unlike other students that his/her aptitude test score fails to be a completely appropriate measure. We consider the problem of using the student's pattern of multiple-choice aptitude test answers to decide whether his/her score is an appropriate ability measure. (Author/CTM)
Descriptors: Answer Sheets, College Entrance Examinations, Guessing (Tests), Latent Trait Theory