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Tugay Kaçak; Abdullah Faruk Kiliç – International Journal of Assessment Tools in Education, 2025
Researchers continue to choose PCA in scale development and adaptation studies because it is the default setting and overestimates measurement quality. When PCA is utilized in investigations, the explained variance and factor loadings can be exaggerated. PCA, in contrast to the models given in the literature, should be investigated in…
Descriptors: Factor Analysis, Monte Carlo Methods, Mathematical Models, Sample Size
Hamilton, Jennifer; Gagne, Phillip E.; Hancock, Gregory R. – 2003
A Monte Carlo simulation approach was taken to investigate the effect of sample size on a variety of latent growth models. A fully balanced experimental design was implemented, with samples drawn from multivariate normal populations specified to represent 12 unique growth models. The models varied factorially by crossing number of time points,…
Descriptors: Mathematical Models, Monte Carlo Methods, Research Methodology, Sample Size
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Spiegel, Douglas K. – Multivariate Behavioral Research, 1986
Tau, Lambda, and Kappa are measures developed for the analysis of discrete multivariate data of the type represented by stimulus response confusion matrices. The accuracy with which they may be estimated from small sample confusion matrices is investigated by Monte Carlo methods. (Author/LMO)
Descriptors: Mathematical Models, Matrices, Monte Carlo Methods, Multivariate Analysis
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Chou, Chih-Ping; Bentler, P. M. – Multivariate Behavioral Research, 1990
The empirical performance under null/alternative hypotheses of the likelihood ratio difference test (LRDT); Lagrange Multiplier test (evaluating the impact of model modification with a specific model); and Wald test (using a general model) were compared. The new tests for covariance structure analysis performed as well as did the LRDT. (RLC)
Descriptors: Analysis of Covariance, Comparative Analysis, Hypothesis Testing, Mathematical Models
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Harwell, Michael R.; And Others – Journal of Educational Statistics, 1992
Implications of metanalytic results from Monte Carlo studies of the robustness of the F test in the one- and two-factor fixed effects analysis of variance (ANOVA) models and Monte Carlo results for the B. L. Welch (1947) and Kruskal-Wallis (1952) tests are discussed. (SLD)
Descriptors: Analysis of Variance, Data Interpretation, Mathematical Models, Meta Analysis
Nigro, George A. – 1970
The applicability of a mathematical theorem designed to trace causality of a three-variable path that consists of an initial cause variable, an intermediate variable, and a final-effect variable with control over other system variables is evaluated. The formula was used with a horizontal rather than a normal distribution, as had been done in an…
Descriptors: Correlation, Educational Research, Mathematical Models, Monte Carlo Methods
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Buja, Andreas; Eyuboglu, Nermin – Multivariate Behavioral Research, 1992
Use of parallel analysis (PA), a selection rule for the number-of-factors problem, is investigated from the viewpoint of permutation assessment through a Monte Carlo simulation. Results reveal advantages and limitations of PA. Tables of sample eigenvalues are included. (SLD)
Descriptors: Computer Simulation, Correlation, Factor Structure, Mathematical Models
Butler, Ronald W. – 1985
The dynamic linear model or Kalman filtering model provides a useful methodology for predicting the past, present, and future states of a dynamic system, such as an object in motion or an economic or social indicator that is changing systematically with time. Recursive likelihood methods for adaptive Kalman filtering and smoothing are developed.…
Descriptors: Algorithms, Estimation (Mathematics), Mathematical Models, Maximum Likelihood Statistics
Elashoff, Janet Dixon; Elashoff, Robert M. – 1971
The problem of comparing proportions when some data are missing is investigated, and determination is made of what statistical techniques are appropriate under each of several probability models describing the observations likely to be missing. Monte Carlo methods were used to investigate the properties of standard estimators under each of the…
Descriptors: Comparative Analysis, Data Analysis, Educational Research, Evaluation Methods
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Harwell, Michael R. – Journal of Educational Statistics, 1992
A methodological framework is provided for quantitatively integrating Type I error rates and power values for Monte Carlo studies. An example is given using Monte Carlo studies of a test of equality of variances, and the importance of relating metanalytic results to exact statistical theory is emphasized. (SLD)
Descriptors: Computer Simulation, Data Interpretation, Mathematical Models, Meta Analysis
Neel, John H. – 1993
Induced probabilities have been largely ignored by educational researchers. Simply stated, if a new or random variable is defined in terms of a first random variable, then induced probability is the probability or density of the new random variable that can be found by summation or integration over the appropriate domains of the original random…
Descriptors: Educational Research, Elementary Secondary Education, Equations (Mathematics), Mathematical Models
Sawilowsky, Shlomo S.; Hillman, Stephen B. – 1991
Psychology studies often have low statistical power. Sample size tables, as given by J. Cohen (1988), may be used to increase power, but they are based on Monte Carlo studies of relatively "tame" mathematical distributions, as compared to psychology data sets. In this study, Monte Carlo methods were used to investigate Type I and Type II…
Descriptors: Mathematical Models, Monte Carlo Methods, Power (Statistics), Psychological Studies
Tracz, Susan M.; Elmore, Patricia B. – 1985
Meta-analysis is a technique for combining the summary statistics from previously conducted research studies to indicate the direction of results and provide an index of the magnitude of effect size. This paper focuses on the effect of the violation of the assumption of independence (that the value of any included statistic is in no way…
Descriptors: Correlation, Effect Size, Mathematical Models, Meta Analysis
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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
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Gallini, Joan K., Mandeville, Garrett K. – Journal of Experimental Education, 1984
This Monte Carlo study examined the validity of the chi-square test for model evaluation in different instances of misspecification and sample size. The usefulness of the chi-square difference statistic to compare competing structures and improvement in fit is also addressed. (Author/BS)
Descriptors: Analysis of Covariance, Error of Measurement, Goodness of Fit, Mathematical Models
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