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Raykov, Tenko; Pusic, Martin – Educational and Psychological Measurement, 2023
This note is concerned with evaluation of location parameters for polytomous items in multiple-component measuring instruments. A point and interval estimation procedure for these parameters is outlined that is developed within the framework of latent variable modeling. The method permits educational, behavioral, biomedical, and marketing…
Descriptors: Item Analysis, Measurement Techniques, Computer Software, Intervals
Holden, Jocelyn E.; Kelley, Ken – Educational and Psychological Measurement, 2010
Classification procedures are common and useful in behavioral, educational, social, and managerial research. Supervised classification techniques such as discriminant function analysis assume training data are perfectly classified when estimating parameters or classifying. In contrast, unsupervised classification techniques such as finite mixture…
Descriptors: Discriminant Analysis, Classification, Computation, Behavioral Science Research
Seco, Guillermo Vallejo; Izquierdo, Marcelino Cuesta; Garcia, M. Paula Fernandez; Diez, F. Javier Herrero – Educational and Psychological Measurement, 2006
The authors compare the operating characteristics of the bootstrap-F approach, a direct extension of the work of Berkovits, Hancock, and Nevitt, with Huynh's improved general approximation (IGA) and the Brown-Forsythe (BF) multivariate approach in a mixed repeated measures design when normality and multisample sphericity assumptions do not hold.…
Descriptors: Sample Size, Comparative Analysis, Simulation, Multivariate Analysis
Kelley, Ken – Educational and Psychological Measurement, 2005
The standardized group mean difference, Cohen's "d", is among the most commonly used and intuitively appealing effect sizes for group comparisons. However, reporting this point estimate alone does not reflect the extent to which sampling error may have led to an obtained value. A confidence interval expresses the uncertainty that exists between…
Descriptors: Intervals, Sampling, Integrity, Effect Size