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Karpman, Mitchell B. – Educational and Psychological Measurement, 1983
This paper explains how a major statistical package (BMDP) can be used to produce partial, semipartial, or bipartial set correlation in terms of a procedure outlined by Karpman (1980). (BW)
Descriptors: Computer Programs, Correlation, Mathematical Models, Multivariate Analysis
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Lambert, Zarrel V.; And Others – Educational and Psychological Measurement, 1991
A method is presented for approximating the amount of bias in estimators with complex sampling distributions that are influenced by a variety of properties. The model is illustrated in the contexts of the bootstrap method and redundancy analysis. (SLD)
Descriptors: Estimation (Mathematics), Mathematical Models, Multivariate Analysis, Sampling
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Berry, Kenneth J.; Mielke, Paul W., Jr. – Educational and Psychological Measurement, 1992
A generalized measure of association and an associated test of significance are presented for nominal independent variables in which any number or combination of interval, ordinal, or nominal dependent variables can be analyzed. A permutation test of significance is provided for the new measure. (SLD)
Descriptors: Correlation, Equations (Mathematics), Mathematical Models, Multivariate Analysis
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Huynh, Huynh – Educational and Psychological Measurement, 1990
Within the multivariate normality framework, a formula is provided for computation of the criterion-related validity of composite scores based on the highest (or lowest) of several equivalent measures. This partial composite score has more validity than each single observation, but less validity than a composite based on all observations. (SLD)
Descriptors: Concurrent Validity, Criterion Referenced Tests, Equations (Mathematics), Mathematical Models
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Wiersma, William; Hall, Charles – Educational and Psychological Measurement, 1973
In the geometrical construct of the MANOVA, the dimensions of interest are primarily those of the significant canonical variates, rather than either those of the original n variables or even the total possible canonical variates. (Authors)
Descriptors: Analysis of Variance, Geometric Concepts, Mathematical Models, Measurement Techniques
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Rupp, Andre A.; Zumbo, Bruno D. – Educational and Psychological Measurement, 2004
Based on seminal work by Lord and Hambleton, Swaminathan, and Rogers, this article is an analytical, graphical, and conceptual reminder that item response theory (IRT) parameter invariance only holds for perfect model fit in multiple populations or across multiple conditions and is thus an ideal state. In practice, one attempts to quantify the…
Descriptors: Correlation, Item Response Theory, Statistical Analysis, Evaluation Methods
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Marcoulides, George A.; Goldstein, Zvi – Educational and Psychological Measurement, 1991
A method is presented for determining the optimal number of conditions to use in measurement designs when resource constraints are imposed. The method is illustrated using a multivariate two-facet design, and extensions to other designs are discussed. (SLD)
Descriptors: Budgeting, Data Collection, Efficiency, Equations (Mathematics)
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Yammarino, Francis J. – Educational and Psychological Measurement, 1990
Relationships among individual- and group-directed measures of leader behavior descriptions and five variables were examined using 54 law enforcement agency personnel associated with a large public university. Data on a questionnaire completed by participants during an interview were studied. Explicit consideration was given to multiple levels of…
Descriptors: Behavior Rating Scales, Comparative Analysis, Equations (Mathematics), Group Dynamics
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Marcoulides, George A.; Goldstein, Zvi – Educational and Psychological Measurement, 1992
A method is presented for determining the optimal number of conditions to use in multivariate-multifacet generalizability designs when resource constraints are imposed. A decision maker can determine the number of observations needed to obtain the largest possible generalizability coefficient. The procedure easily applies to the univariate case.…
Descriptors: Budgeting, Cost Effectiveness, Decision Making, Equations (Mathematics)