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Levin, Joseph – Multivariate Behavioral Research, 1986
The relation between the power of a significance test in a block design with correlated measurements and the reliability of the measuring instrument is analyzed in terms of the components of variance entering the reliability coefficient and the noncentrality parameter. (Author/LMO)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Power (Statistics)
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Blumberg, Carol Joyce; Porter, Andrew C. – Journal of Experimental Education, 1983
The general class of continuous growth models are described and examples representative of growth models suggested for various types of academic and/or physical growth are given. The fan spread hypothesis is discussed in relationship to natural growth models, as well as differential linear growth. (PN)
Descriptors: Achievement Gains, Data Analysis, Evaluation Methods, Hypothesis Testing
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Bird, Kevin D. – Educational and Psychological Measurement, 1991
A method is outlined for analysis of the shape of an individual profile of scores on a standardized test battery. The method uses a simultaneous test procedure allowing for an overall test of profile flatness, with follow-up tests on all contrasts of interest. (SLD)
Descriptors: Equations (Mathematics), Hypothesis Testing, Mathematical Models, Profiles
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Lam, Tony C. M. – 1981
The objective of this paper is to examine the relationship between the unreliability of difference scores and the power of tests of significance in an attempt to determine the validity of the paradox for the measurement of change presented by Overall and Woodward: that the power of tests of significance is maximum when the reliability of the…
Descriptors: Achievement Gains, Correlation, Error of Measurement, Hypothesis Testing
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Zwick, Rebecca – Multivariate Behavioral Research, 1986
The purpose of the current study was to investigate the relative performance of the parametric, rank, and normal scores procedures when the classical assumptions were met and under violations of these assumptions. This investigation included the normal scores as well as the rank test. (LMO)
Descriptors: Hypothesis Testing, Mathematical Models, Measurement Techniques, Monte Carlo Methods
Corder-Bolz, Charles R. – 1978
A Monte Carlo Study was conducted to evaluate six models commonly used to evaluate change. The results revealed specific problems with each. Analysis of covariance and analysis of variance of residualized gain scores appeared to substantially and consistently overestimate the change effects. Multiple factor analysis of variance models utilizing…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Hypothesis Testing
Peer reviewed Peer reviewed
Preece, Peter F. W. – Educational and Psychological Measurement, 1982
The validity of various reliability-corrected procedures for adjusting for initial differences between groups in uncontrolled studies is established for subjects exhibiting linear fan-spread growth. The results are then extended to a nonlinear model of growth. (Author)
Descriptors: Achievement Gains, Analysis of Covariance, Error of Measurement, Hypothesis Testing
Peer reviewed Peer reviewed
Hakstian, A. Ralph; And Others – Psychometrika, 1988
A model and computation procedure based on classical test score theory are presented for determination of a correlation coefficient corrected for attenuation due to unreliability. Delta and Monte Carlo method applications are discussed. A power analysis revealed no serious loss in efficiency resulting from correction for attentuation. (TJH)
Descriptors: Correlation, Equations (Mathematics), Hypothesis Testing, Mathematical Models
Levine, Michael V.; Drasgow, Fritz – 1984
Some examinees' test-taking behavior may be so idiosyncratic that their scores are not comparable to the scores of more typical examinees. Appropriateness indices, which provide quantitative measures of response-pattern atypicality, can be viewed as statistics for testing a null hypothesis of normal test-taking behavior against an alternative…
Descriptors: Cheating, College Entrance Examinations, Computer Simulation, Estimation (Mathematics)
Echternacht, Gary; Swinton, Spencer – 1979
Title I evaluations using the RMC Model C design depend for their interpretation on the assumption that the regression of posttest on pretest is linear across the cut score level when there is no treatment; but there are many instances where nonlinearities may occur. If one applies the analysis of covariance, or model C analysis, large errors may…
Descriptors: Achievement Gains, Analysis of Covariance, Educational Assessment, Elementary Secondary Education