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Hakstian, A. Ralph; Barchard, Kimberly A. – Multivariate Behavioral Research, 2000
Developed a sample-based nonanalytical degrees-of-freedom correction factor for situations sampling both subjects and conditions with measurement data departing from essentially parallel form. Assessed the application of this correction factor through a simulation study involving data sets with a range of design characteristics and manifesting…
Descriptors: Robustness (Statistics), Sampling, Simulation, Statistical Inference
Peer reviewed Peer reviewed
Barchard, Kimberly A.; Hakstian, A. Ralph – Educational and Psychological Measurement, 1997
The distinction between Type 1 and Type 12 sampling in connection with measurement data is discussed, and a method is presented for simulating data arising from Type 12 sampling. A Monte Carlo study is described that shows conditions under which precise confidence level control under Type 12 sampling is maintained. (SLD)
Descriptors: Models, Monte Carlo Methods, Sampling, Simulation
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Schroeder, Marsha L.; Hakstian, A. Ralph – Psychometrika, 1990
A 2-facet measurement model is identified, and its coefficient of generalizability (CG) is examined. Three other multifaceted measurement models and their CGs are identified. An empirical investigation of all four procedures is conducted using data from a study of the psychopathology of 71 prison inmates. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Generalizability Theory, Mathematical Models
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Hakstian, A. Ralph; And Others – Psychometrika, 1989
Four measurement designs are presented for use with correlation coefficients corrected, in one variable, for attenuation due to unreliability (partially disattenuated). Associated asymptotic variance/covariance expressions are presented. Empirical simulation results illustrate the satisfactory Type I error control and statistical power of the…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Equations (Mathematics)
Peer reviewed Peer reviewed
Hakstian, A. Ralph; And Others – Psychometrika, 1988
A model and computation procedure based on classical test score theory are presented for determination of a correlation coefficient corrected for attenuation due to unreliability. Delta and Monte Carlo method applications are discussed. A power analysis revealed no serious loss in efficiency resulting from correction for attentuation. (TJH)
Descriptors: Correlation, Equations (Mathematics), Hypothesis Testing, Mathematical Models