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Rozeboom, William W. – Psychometrika, 1979
For idealized item configurations, equal item weights are often virtually as good for a particular predictive purpose as the item weights that are theoretically optimal. What has not been clear, however, is what happens to the similarity when the item configuration's variance structure is complex. (Author/CTM)
Descriptors: Multiple Regression Analysis, Predictor Variables, Scoring Formulas, Weighted Scores
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MacCann, Robert G. – Psychometrika, 2004
For (0, 1) scored multiple-choice tests, a formula giving test reliability as a function of the number of item options is derived, assuming the "knowledge or random guessing model," the parallelism of the new and old tests (apart from the guessing probability), and the assumptions of classical test theory. It is shown that the formula is a more…
Descriptors: Guessing (Tests), Multiple Choice Tests, Test Reliability, Test Theory
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Austin, Joe Dan – Psychometrika, 1981
On distractor-identification tests students mark as many distractors as possible on each test item. A grading scale is developed for this type testing. The score is optimal in that it yields an unbiased estimate of the student's score as if no guessing had occurred. (Author/JKS)
Descriptors: Guessing (Tests), Item Analysis, Measurement Techniques, Scoring Formulas
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Duncan, George T.; Milton, E. O. – Psychometrika, 1978
A multiple-answer multiple-choice test is one which offers several alternate choices for each stem and any number of those choices may be considered to be correct. In this article, a class of scoring procedures called the binary class is discussed. (Author/JKS)
Descriptors: Answer Keys, Measurement Techniques, Multiple Choice Tests, Scoring Formulas