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Zhang, Jinming – Applied Psychological Measurement, 2012
It is common to assume during a statistical analysis of a multiscale assessment that the assessment is composed of several unidimensional subtests or that it has simple structure. Under this assumption, the unidimensional and multidimensional approaches can be used to estimate item parameters. These two approaches are equivalent in parameter…
Descriptors: Simulation, Computation, Models, Statistical Analysis
Gu, Fei; Skorupski, William P.; Hoyle, Larry; Kingston, Neal M. – Applied Psychological Measurement, 2011
Ramsay-curve item response theory (RC-IRT) is a nonparametric procedure that estimates the latent trait using splines, and no distributional assumption about the latent trait is required. For item parameters of the two-parameter logistic (2-PL), three-parameter logistic (3-PL), and polytomous IRT models, RC-IRT can provide more accurate estimates…
Descriptors: Intervals, Item Response Theory, Models, Evaluation Methods
de la Torre, Jimmy; Hong, Yuan – Applied Psychological Measurement, 2010
Sample size ranks as one of the most important factors that affect the item calibration task. However, due to practical concerns (e.g., item exposure) items are typically calibrated with much smaller samples than what is desired. To address the need for a more flexible framework that can be used in small sample item calibration, this article…
Descriptors: Sample Size, Markov Processes, Tests, Data Analysis
de la Torre, Jimmy; Song, Hao – Applied Psychological Measurement, 2009
Assessments consisting of different domains (e.g., content areas, objectives) are typically multidimensional in nature but are commonly assumed to be unidimensional for estimation purposes. The different domains of these assessments are further treated as multi-unidimensional tests for the purpose of obtaining diagnostic information. However, when…
Descriptors: Ability, Tests, Item Response Theory, Data Analysis
Effects of Ignoring Item Interaction on Item Parameter Estimation and Detection of Interacting Items
Chen, Cheng-Te; Wang, Wen-Chung – Applied Psychological Measurement, 2007
This study explores the effects of ignoring item interaction on item parameter estimation and the efficiency of using the local dependence index Q[subscript 3] and the SAS NLMIXED procedure to detect item interaction under the three-parameter logistic model and the generalized partial credit model. Through simulations, it was found that ignoring…
Descriptors: Models, Item Response Theory, Simulation, Generalization
Zhang, Bo; Walker, Cindy M. – Applied Psychological Measurement, 2008
The purpose of this research was to examine the effects of missing data on person-model fit and person trait estimation in tests with dichotomous items. Under the missing-completely-at-random framework, four missing data treatment techniques were investigated including pairwise deletion, coding missing responses as incorrect, hotdeck imputation,…
Descriptors: Item Response Theory, Computation, Goodness of Fit, Test Items
Habing, Brian; Finch, Holmes; Roberts, James S. – Applied Psychological Measurement, 2005
Although there are many methods available for dimensionality assessment for items with monotone item response functions, there are few methods available for unfolding item response theory models. In this study, a modification of Yen's Q3 statistic is proposed for the case of these nonmonotone item response models. Through a simulation study, the…
Descriptors: Data Analysis, Simulation, Multidimensional Scaling, Item Response Theory

Bockenholt, Ulf; Bockenholt, Ingo – Applied Psychological Measurement, 1990
A latent-class scaling approach is presented for modeling paired comparison and "pick any/t" data obtained in preference studies. The utility of this approach is demonstrated through analysis of data from studies involving consumer preference and preference for political candidates. (SLD)
Descriptors: Comparative Analysis, Consumer Economics, Data Analysis, Equations (Mathematics)

McFatter, Robert M. – Applied Psychological Measurement, 1979
The usual interpretation of suppressor effects in a multiple regression equation assumes that the correlations among variables have been generated by a particular structural model. How such a regression equation is interpreted is shown to be dependent on the structural model deemed appropriate. (Author/JKS)
Descriptors: Correlation, Critical Path Method, Data Analysis, Models

Humphreys, Lloyd G.: And Others – Applied Psychological Measurement, 1979
A simplex process model of the cross-lagged correlation paradigm was applied to 16 tests administered to samples of Black and White males and females in grades 5, 7, 9, and 11. Relationships among the measures as well as the use of the model are discussed. (Author/JKS)
Descriptors: Academic Achievement, Achievement Tests, Data Analysis, Elementary Secondary Education