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Fleiss, Joseph L.; Shrout, Patrick E. – Psychometrika, 1978
When raters in a reliability study are a random sample, inferences about the intraclass correlation coefficient must be based on three mean squares from the analysis of variance: between subjects, between raters, and error. An approximate confidence interval for the parameter is presented as a function of these mean squares. (Author/JKS)
Descriptors: Analysis of Variance, Correlation, Measurement Techniques, Rating Scales
Peer reviewed Peer reviewed
Joe, George W.; Woodward, J. Arthur – Psychometrika, 1976
This article is concerned with estimation of components of maximum generalizability in multifacet experimental designs involving multiple dependent measures. An example of a two-facet partially nested design is provided. (Author/RC)
Descriptors: Analysis of Variance, Correlation, Matrices, Reliability
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Kraemer, Helena Chmura – Psychometrika, 1981
Limitations and extensions of Feldt's approach to testing the equality of Cronbach's alpha coefficients in independent and matched samples are discussed. In particular, this approach is used to test equality of intraclass correlation coefficients. (Author)
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Mathematical Models
Peer reviewed Peer reviewed
Hakstian, A. Ralph; Whalen, Thomas E. – Psychometrika, 1976
Details of a reasonably precise normalization technique for coefficient alpha are outlined, along with methods for estimating the variance of the normalized statistic. These procedures lead to the K-sample significance test. (RC)
Descriptors: Analysis of Variance, Comparative Analysis, Error Patterns, Hypothesis Testing
Peer reviewed Peer reviewed
Novick, Melvin R.; And Others – Psychometrika, 1971
Descriptors: Analysis of Variance, Bayesian Statistics, Error of Measurement, Mathematical Models
Peer reviewed Peer reviewed
Woodruff, David J.; Feldt, Leonard S. – Psychometrika, 1986
This paper presents 11 statistical procedures which test the equality of m coefficient alphas when the sample alpha coefficients are dependent. Several of the procedures are derived in detail, and numerical examples are given for two. (Author/LMO)
Descriptors: Analysis of Covariance, Analysis of Variance, Computer Simulation, Hypothesis Testing