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Forsyth, Robert A. – Applied Psychological Measurement, 1978
This note shows that, under conditions specified by Levin and Subkoviak (TM 503 420), it is not necessary to specify the reliabilities of observed scores when comparing completely randomized designs with randomized block designs. Certain errors in their illustrative example are also discussed. (Author/CTM)
Descriptors: Analysis of Variance, Error of Measurement, Hypothesis Testing, Reliability

Levin, Joel R.; Subkoviak, Michael J. – Applied Psychological Measurement, 1978
Comments (TM 503 706) on an earlier article (TM 503 420) concerning the comparison of the completely randomized design and the randomized block design are acknowledged and appreciated. In addition, potentially misleading notions arising from these comments are addressed and clarified. (See also TM 503 708). (Author/CTM)
Descriptors: Analysis of Variance, Error of Measurement, Hypothesis Testing, Reliability

Forsyth, Robert A. – Applied Psychological Measurement, 1978
This note continues the discussion of earlier articles (TM 503 420, TM 503 706, and TM 503 707), comparing the completely randomized design with the randomized block design. (CTM)
Descriptors: Analysis of Variance, Error of Measurement, Hypothesis Testing, Reliability

Berger, Martjin P. F. – Applied Psychological Measurement, 1991
A generalized variance criterion is proposed to measure efficiency in item-response-theory (IRT) models. Heuristic arguments are given to formulate the efficiency of a design in terms of an asymptotic generalized variance criterion. Efficiencies of designs for one-, two-, and three-parameter models are compared. (SLD)
Descriptors: Comparative Analysis, Efficiency, Equations (Mathematics), Error of Measurement

Levin, Joel R.; Subkoviak, Michael J. – Applied Psychological Measurement, 1977
Textbook calculations of statistical power or sample size follow from formulas that assume that the variables under consideration are measured without error. However, in the real world of behavioral research, errors of measurement cannot be neglected. The determination of sample size is discussed, and an example illustrates blocking strategy.…
Descriptors: Analysis of Covariance, Analysis of Variance, Error of Measurement, Hypothesis Testing