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Willse, John T. – Measurement and Evaluation in Counseling and Development, 2017
This article provides a brief introduction to the Rasch model. Motivation for using Rasch analyses is provided. Important Rasch model concepts and key aspects of result interpretation are introduced, with major points reinforced using a simulation demonstration. Concrete guidelines are provided regarding sample size and the evaluation of items.
Descriptors: Item Response Theory, Test Results, Test Interpretation, Simulation
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Fu, Yanyan; Strachan, Tyler; Ip, Edward H.; Willse, John T.; Chen, Shyh-Huei; Ackerman, Terry – International Journal of Testing, 2020
This research examined correlation estimates between latent abilities when using the two-dimensional and three-dimensional compensatory and noncompensatory item response theory models. Simulation study results showed that the recovery of the latent correlation was best when the test contained 100% of simple structure items for all models and…
Descriptors: Item Response Theory, Models, Test Items, Simulation
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Willse, John T. – Educational and Psychological Measurement, 2011
This research provides a demonstration of the utility of mixture Rasch models. Specifically, a model capable of estimating a mixture partial credit model using joint maximum likelihood is presented. Like the partial credit model, the mixture partial credit model has the beneficial feature of being appropriate for analysis of assessment data…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Computation, College Seniors
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Strachan, Tyler; Cho, Uk Hyun; Kim, Kyung Yong; Willse, John T.; Chen, Shyh-Huei; Ip, Edward H.; Ackerman, Terry A.; Weeks, Jonathan P. – Journal of Educational Measurement, 2021
In vertical scaling, results of tests from several different grade levels are placed on a common scale. Most vertical scaling methodologies rely heavily on the assumption that the construct being measured is unidimensional. In many testing situations, however, such an assumption could be problematic. For instance, the construct measured at one…
Descriptors: Item Response Theory, Scaling, Tests, Construct Validity
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Ip, Edward H.; Strachan, Tyler; Fu, Yanyan; Lay, Alexandra; Willse, John T.; Chen, Shyh-Huei; Rutkowski, Leslie; Ackerman, Terry – Journal of Educational Measurement, 2019
Test items must often be broad in scope to be ecologically valid. It is therefore almost inevitable that secondary dimensions are introduced into a test during test development. A cognitive test may require one or more abilities besides the primary ability to correctly respond to an item, in which case a unidimensional test score overestimates the…
Descriptors: Test Items, Test Bias, Test Construction, Scores
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Myers, Jane E.; Willse, John T.; Villalba, Jose A. – Journal of Counseling & Development, 2011
To assess the extent to which holistic wellness factors are predictive of self-esteem, the authors administered the Coopersmith Self-Esteem Inventories, School Form (Coopersmith, 2002), and the Five Factor Wellness Inventory (Myers & Sweeney, 2005a) to 225 adolescents ages 15 to 17 years. Wellness factors (Coping Self, Social Self, and…
Descriptors: Adolescents, Self Esteem, Wellness, Coping
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Wester, Kelly L.; Willse, John T.; Davis, Mark S. – Counselor Education and Supervision, 2010
In this quantitative study, 187 counselor educators at research institutions reported engaging in responsible conduct of research (RCR), with a few individuals reporting deviations from ethical behavior. Tenure-seeking faculty members indicated a greater likelihood of deviating from acceptable research practices than did tenured faculty members.…
Descriptors: Integrity, Psychology, Counseling, Ethics
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Goodman, Joshua T.; Willse, John T.; Allen, Nancy L.; Klaric, John S. – Educational and Psychological Measurement, 2011
The Mantel-Haenszel procedure is a popular technique for determining items that may exhibit differential item functioning (DIF). Numerous studies have focused on the strengths and weaknesses of this procedure, but few have focused the performance of the Mantel-Haenszel method when structurally missing data are present as a result of test booklet…
Descriptors: Test Bias, Identification, Tests, Test Length
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Willse, John T.; Goodman, Joshua T. – Educational and Psychological Measurement, 2008
This research provides a direct comparison of effect size estimates based on structural equation modeling (SEM), item response theory (IRT), and raw scores. Differences between the SEM, IRT, and raw score approaches are examined under a variety of data conditions (IRT models underlying the data, test lengths, magnitude of group differences, and…
Descriptors: Test Length, Structural Equation Models, Effect Size, Raw Scores
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Henson, Robert A.; Templin, Jonathan L.; Willse, John T. – Psychometrika, 2009
This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for…
Descriptors: Identification, Probability, Item Response Theory, Mastery Tests
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Fulcher, Keston H.; Willse, John T. – Assessment Update, 2007
Value added has emerged as a hot-button topic in the assessment literature, due in large part to the Commission on the Future of Higher Education. Value added, as conceptualized by Astin (1985), reflects talent development, "changes in the student from the beginning to the end of an educational program. These changes can cover a wide range of…
Descriptors: Higher Education, Intervention, Pretests Posttests, Error of Measurement
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Willse, John T.; Goodman, Joshua T.; Allen, Nancy; Klaric, John – Applied Measurement in Education, 2008
The current research demonstrates the effectiveness of using structural equation modeling (SEM) for the investigation of subgroup differences with sparse data designs where not every student takes every item. Simulations were conducted that reflected missing data structures like those encountered in large survey assessment programs (e.g., National…
Descriptors: Structural Equation Models, Simulation, Item Response Theory, Factor Analysis
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Sivo, Stephen A.; Xitao, Fan; Witta, E. Lea; Willse, John T. – Journal of Experimental Education, 2006
This study is a partial replication of L. Hu and P. M. Bentler's (1999) fit criteria work. The purpose of this study was twofold: (a) to determine whether cut-off values vary according to which model is the true population model for a dataset and (b) to identify which of 13 fit indexes behave optimally by retaining all of the correct models while…
Descriptors: Structural Equation Models, Goodness of Fit, Criteria, Sample Size