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van der Linden, Wim J. – Applied Psychological Measurement, 2011
It is shown how the time limit on a test can be set to control the probability of a test taker running out of time before completing it. The probability is derived from the item parameters in the lognormal model for response times. Examples of curves representing the probability of running out of time on a test with given parameters as a function…
Descriptors: Testing, Timed Tests, Models, Probability
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Kahraman, Nilufer; Cuddy, Monica M.; Clauser, Brian E. – Applied Psychological Measurement, 2013
This research explores the usefulness of latent growth curve modeling in the study of pacing behavior and test speededness. Examinee response times from a high-stakes, computerized examination, collected before and after the examination was subjected to a timing change, were analyzed using a series of latent growth curve models to detect…
Descriptors: Pacing, Models, Reaction Time, Timed Tests
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Semmes, Robert; Davison, Mark L.; Close, Catherine – Applied Psychological Measurement, 2011
If numerical reasoning items are administered under time limits, will two dimensions be required to account for the responses, a numerical ability dimension and a speed dimension? A total of 182 college students answered 74 numerical reasoning items. Every item was taken with and without time limits by half the students. Three psychometric models…
Descriptors: Individual Differences, Logical Thinking, Timed Tests, College Students
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van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – Applied Psychological Measurement, 1999
Proposes an item-selection algorithm for neutralizing the differential effects of time limits on computerized adaptive test scores. Uses a statistical model for distributions of examinees' response times on items in a bank that is updated each time an item is administered. Demonstrates the method using an item bank from the Armed Services…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
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Whitely, Susan E. – Applied Psychological Measurement, 1979
A model which gives maximum likelihood estimates of measurement error within the context of a simplex model for practice effects is presented. The appropriateness of the model is tested for five traits, and error estimates are compared to the classical formula estimates. (Author/JKS)
Descriptors: Error of Measurement, Error Patterns, Higher Education, Mathematical Models