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Muth, Chelsea; Bales, Karen L.; Hinde, Katie; Maninger, Nicole; Mendoza, Sally P.; Ferrer, Emilio – Educational and Psychological Measurement, 2016
Unavoidable sample size issues beset psychological research that involves scarce populations or costly laboratory procedures. When incorporating longitudinal designs these samples are further reduced by traditional modeling techniques, which perform listwise deletion for any instance of missing data. Moreover, these techniques are limited in their…
Descriptors: Sample Size, Psychological Studies, Models, Statistical Analysis
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Aiken, Lewis R. – Educational and Psychological Measurement, 1985
Three numerical coefficients for analyzing the validity and reliability of ratings are described. Each coefficient is computed as the ratio of an obtained to a maximum sum of differences in ratings. The coefficients are also applicable to the item analysis, agreement analysis, and cluster or factor analysis of rating-scale data. (Author/BW)
Descriptors: Computer Software, Data Analysis, Factor Analysis, Item Analysis
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Krus, David J.; Liang, Kun-Hsia T. – Educational and Psychological Measurement, 1984
An algorithm for estimation of means and standard deviations or raw scores underlying table values of standard test scores is presented. An application of a computer program, operationalizing the suggested algorithm, is discussed within the framework of a comparison of estimated and known table values for sample Minnesota Multiphasic Personality…
Descriptors: Algorithms, Estimation (Mathematics), Scores, Standardized Tests
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Hinkle, Dennis E.; Oliver, J. Dale – Educational and Psychological Measurement, 1983
In this paper, tables for the appropriate sample sizes are presented and discussed in the context that the determination of the effect size must precede the determination of the sample size. (Author/PN)
Descriptors: Effect Size, Research Methodology, Research Needs, Research Problems
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Vegelius, Jan – Educational and Psychological Measurement, 1981
The G index is a measure of the similarity between individuals over dichotomous items. Some tests for the G-index are described. For each case an example is included. (Author/GK)
Descriptors: Hypothesis Testing, Mathematical Formulas, Mathematical Models, Nonparametric Statistics
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Dutoit, Eugene F.; Penfield, Douglas A. – Educational and Psychological Measurement, 1979
Assuming a multiple linear regression model with q independent variables, a procedure is developed for determining the minimum statistically significant increase in the multiple correlation coefficient when an additional independent variable is considered for regression. The procedure is presented analytically and in table form. Examples are…
Descriptors: Correlation, Multiple Regression Analysis, Predictor Variables, Tables (Data)
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Wilcox, Rand R. – Educational and Psychological Measurement, 1980
When analyzing a squared multiple correlation coefficient, an investigator may be interested in determining whether it is above or below a known constant, rather than testing the null hypothesis. This paper gives the sample sizes required for answering this question when indifference zone formulation of the problem is used. (Author/BW)
Descriptors: Correlation, Hypothesis Testing, Sampling
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Zalinski, James; And Others – Educational and Psychological Measurement, 1979
A set of tables for determining tetrachoric correlations is presented. The coefficients have been determined to three-decimal accuracy. (JKS)
Descriptors: Correlation, Expectancy Tables, Nonparametric Statistics, Tables (Data)