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Wanstrom, Linda – Multivariate Behavioral Research, 2009
Second-order latent growth curve models (S. C. Duncan & Duncan, 1996; McArdle, 1988) can be used to study group differences in change in latent constructs. We give exact formulas for the covariance matrix of the parameter estimates and an algebraic expression for the estimation of slope differences. Formulas for calculations of the required sample…
Descriptors: Sample Size, Effect Size, Mathematical Formulas, Computation
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Snijders, Tom A. B. – Psychometrika, 1991
A complete enumeration method and a Monte Carlo method are presented to calculate the probability distribution of arbitrary statistics of adjacency matrices when these matrices have the uniform distribution conditional on given row and column sums, and possibly on a given set of structural zeros. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Mathematical Models, Matrices
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Reddon, John R.; And Others – Journal of Educational Statistics, 1985
Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)
Descriptors: Computer Simulation, Correlation, Error of Measurement, Matrices
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Lautenschlager, Gary J.; And Others – Educational and Psychological Measurement, 1989
A method for estimating the first eigenvalue of random data correlation matrices is reported, and its precision is demonstrated via comparison to the method of S. J. Allen and R. Hubbard (1986). Data generated in Monte Carlo simulations with 10 sample sizes reaching up to 1,000 were used. (SLD)
Descriptors: Computer Simulation, Correlation, Equations (Mathematics), Estimation (Mathematics)
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Thompson, Bruce – Journal of Experimental Education, 1991
Monte Carlo methods were used to evaluate the degree to which canonical function and structure coefficients may be differentially sensitive to sampling error. For each of 64 research situations, 1,000 random samples were drawn. Both sets of coefficients were roughly equally influenced; some exceptions are noted. (SLD)
Descriptors: Behavioral Science Research, Computer Simulation, Correlation, Matrices
Kaplan, David – 1993
The impact of the use of data arising from balanced incomplete block (BIB) spiralled designs on the chi-square goodness-of-fit test in factor analysis is considered. Data from BIB designs posses a unique pattern of missing data that can be characterized as missing completely at random (MCAR). Standard approaches to factor analyzing such data rest…
Descriptors: Chi Square, Computer Simulation, Correlation, Factor Analysis
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Brown, R. L. – Educational and Psychological Measurement, 1989
Three correlation matrices (PEARSON, POLYCHORIC, and TOBIT) were used to obtain reliability estimates on ordered polytomous variable models. A Monte Carlo study with different levels of variable asymmetry and 400 sample correlation matrices demonstrated that the PEARSON matrix did not perform as well as did the other 2 matrices. (SLD)
Descriptors: Analysis of Covariance, Comparative Analysis, Computer Simulation, Correlation
Beasley, T. Mark; Leitner, Dennis W. – 1994
The use of stepwise regression has been criticized for both interpretive misunderstandings and statistical aberrations. A major statistical problem with stepwise regression and other procedures that involve multiple significance tests is the inflation of the Type I error rate. General approaches to control the family-wise error rate such as the…
Descriptors: Algorithms, Computer Simulation, Correlation, Error of Measurement
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Kloot, Willem A. van der; Herk, Hester van – Multivariate Behavioral Research, 1991
Two sets of real sorting data from 50 college students are used to compare results of multidimensional scaling of raw co-occurrence frequencies or dissimilarity measures (D) and profile distances (delta) to determine which yields a better representation of the underlying structure of 2 sets of stimuli. Slight differences are discussed. (SLD)
Descriptors: Classification, Cognitive Processes, College Students, Comparative Analysis