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Cheng, Ying; Chen, Peihua; Qian, Jiahe; Chang, Hua-Hua – Applied Psychological Measurement, 2013
Differential item functioning (DIF) analysis is an important step in the data analysis of large-scale testing programs. Nowadays, many such programs endorse matrix sampling designs to reduce the load on examinees, such as the balanced incomplete block (BIB) design. These designs pose challenges to the traditional DIF analysis methods. For example,…
Descriptors: Test Bias, Equated Scores, Test Items, Effect Size
Cho, Sun-Joo; Cohen, Allan S.; Kim, Seock-Ho; Bottge, Brian – Applied Psychological Measurement, 2010
A latent transition analysis (LTA) model was described with a mixture Rasch model (MRM) as the measurement model. Unlike the LTA, which was developed with a latent class measurement model, the LTA-MRM permits within-class variability on the latent variable, making it more useful for measuring treatment effects within latent classes. A simulation…
Descriptors: Item Response Theory, Measurement, Models, Statistical Analysis

Meijer, Rob R. – Applied Psychological Measurement, 1995
A statistic used by R. Meijer (1994) to determine person-fit referred to the number of errors from the deterministic Guttman model (L. Guttman, 1950), but this was, in fact, based on the number of errors from the deterministic Guttman model as defined by J. Loevinger (1947, 1948). (SLD)
Descriptors: Difficulty Level, Models, Responses, Scaling

Liou, Michelle – Applied Psychological Measurement, 1988
In applying I. I. Bejar's method for detecting the dimensionality of achievement tests, researchers should be cautious in interpreting the slope of the principal axis. Other information from the data is needed in conjunction with Bejar's method of addressing item dimensionality. (SLD)
Descriptors: Achievement Tests, Computer Simulation, Difficulty Level, Equated Scores

van der Linden, Wim J. – Applied Psychological Measurement, 1979
The restrictions on item difficulties that must be met when binomial models are applied to domain-referenced testing are examined. Both a deterministic and a stochastic conception of item responses are discussed with respect to difficulty and Guttman-type items. (Author/BH)
Descriptors: Difficulty Level, Item Sampling, Latent Trait Theory, Mathematical Models