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Chiu, Ting-Wei; Camilli, Gregory – Applied Psychological Measurement, 2013
Guessing behavior is an issue discussed widely with regard to multiple choice tests. Its primary effect is on number-correct scores for examinees at lower levels of proficiency. This is a systematic error or bias, which increases observed test scores. Guessing also can inflate random error variance. Correction or adjustment for guessing formulas…
Descriptors: Item Response Theory, Guessing (Tests), Multiple Choice Tests, Error of Measurement
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Doebler, Anna – Applied Psychological Measurement, 2012
It is shown that deviations of estimated from true values of item difficulty parameters, caused for example by item calibration errors, the neglect of randomness of item difficulty parameters, testlet effects, or rule-based item generation, can lead to systematic bias in point estimation of person parameters in the context of adaptive testing.…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computation, Item Response Theory
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Hung, Lai-Fa – Applied Psychological Measurement, 2012
Rasch used a Poisson model to analyze errors and speed in reading tests. An important property of the Poisson distribution is that the mean and variance are equal. However, in social science research, it is very common for the variance to be greater than the mean (i.e., the data are overdispersed). This study embeds the Rasch model within an…
Descriptors: Social Science Research, Markov Processes, Reading Tests, Social Sciences
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Attali, Yigal – Applied Psychological Measurement, 2011
Recently, Attali and Powers investigated the usefulness of providing immediate feedback on the correctness of answers to constructed response questions and the opportunity to revise incorrect answers. This article introduces an item response theory (IRT) model for scoring revised responses to questions when several attempts are allowed. The model…
Descriptors: Feedback (Response), Item Response Theory, Models, Error Correction
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Finkelman, Matthew D.; Weiss, David J.; Kim-Kang, Gyenam – Applied Psychological Measurement, 2010
Assessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC…
Descriptors: Computer Assisted Testing, Hypothesis Testing, Measurement, Item Analysis
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Roberts, James S. – Applied Psychological Measurement, 2008
Orlando and Thissen (2000) developed an item fit statistic for binary item response theory (IRT) models known as S-X[superscript 2]. This article generalizes their statistic to polytomous unfolding models. Four alternative formulations of S-X[superscript 2] are developed for the generalized graded unfolding model (GGUM). The GGUM is a…
Descriptors: Item Response Theory, Goodness of Fit, Test Items, Models
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Cohen, Jon; Chan, Tsze; Jiang, Tao; Seburn, Mary – Applied Psychological Measurement, 2008
U.S. state educational testing programs administer tests to track student progress and hold schools accountable for educational outcomes. Methods from item response theory, especially Rasch models, are usually used to equate different forms of a test. The most popular method for estimating Rasch models yields inconsistent estimates and relies on…
Descriptors: Testing Programs, Educational Testing, Item Response Theory, Computation