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Rousseau, Ronald – Information Processing and Management, 1992
This article offers comments and clarifications of Egghe's paper, which dealt with information production processes (IPP) and the Gini index. Topics addressed include the length of the Lorenz curve as a concentration measure, the discrete duality operator, and a Bradford-Leimkuhler distribution. (10 references) (LRW)
Descriptors: Information Science, Mathematical Formulas, Mathematical Models, Measurement Techniques

Burrell, Quentin L. – Information Processing and Management, 1992
Investigates the Leimkuhler curve and the Gini index from a probabilistic viewpoint for studying the concentration of bibliometric distributions. The importance of the time parameter and the special nature of the "nonproducers" in bibliometric studies are examined, standard models of bibliometric processes are described, and further…
Descriptors: Bibliometrics, Mathematical Formulas, Mathematical Models, Measurement Techniques

Alsawalmeh, Yousef M.; Feldt, Leonard S. – Applied Psychological Measurement, 1992
An approximate statistical test is derived for the hypothesis that the intraclass reliability coefficients associated with two measurement procedures are equal. Control of Type 1 error is investigated by comparing empirical sampling distributions of the test statistic with its derived theoretical distribution. A numerical illustration is…
Descriptors: Equations (Mathematics), Hypothesis Testing, Mathematical Models, Measurement Techniques
Zwick, Rebecca – 1986
Most currently used measures of inter-rater agreement for the nominal case incorporate a correction for "chance agreement." The definition of chance agreement is not the same for all coefficients, however. Three chance-corrected coefficients are Cohen's Kappa; Scott's Pi; and the S index of Bennett, Goldstein, and Alpert, which has…
Descriptors: Error of Measurement, Interrater Reliability, Mathematical Models, Measurement Techniques

Millsap, Roger E.; Everson, Howard – Multivariate Behavioral Research, 1991
Use of confirmatory factor analysis (CFA) with nonzero latent means in testing six different measurement models from classical test theory is discussed. Implications of the six models for observed mean and covariance structures are described, and three examples of the use of CFA in testing the models are presented. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Goodness of Fit, Mathematical Models