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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
Lingbo Tong; Wen Qu; Zhiyong Zhang – Grantee Submission, 2025
Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…
Descriptors: Factor Analysis, Monte Carlo Methods, Statistical Analysis, Sample Size
Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying – Research Quarterly for Exercise and Sport, 2011
Monte Carlo methods can be used in data analytic situations (e.g., validity studies) to make decisions about sample size and to estimate power. The purpose of using Monte Carlo methods in a validity study is to improve the methodological approach within a study where the primary focus is on construct validity issues and not on advancing…
Descriptors: Sample Size, Monte Carlo Methods, Construct Validity, Validity
Bowler, Mark C.; Woehr, David J. – Journal of Vocational Behavior, 2009
Recent Monte Carlo research has illustrated that the traditional method for assessing the construct-related validity of assessment center (AC) post-exercise dimension ratings (PEDRs), an application of confirmatory factor analysis (CFA) to a multitrait-multimethod matrix, produces inconsistent results [Lance, C. E., Woehr, D. J., & Meade, A. W.…
Descriptors: Monte Carlo Methods, Multitrait Multimethod Techniques, Construct Validity, Validity
de Winter, J. C. F.; Dodou, D.; Wieringa, P. A. – Multivariate Behavioral Research, 2009
Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different…
Descriptors: Sample Size, Factor Analysis, Enrollment, Evaluation Methods
Yoo, Jin Eun – Educational and Psychological Measurement, 2009
This Monte Carlo study investigates the beneficiary effect of including auxiliary variables during estimation of confirmatory factor analysis models with multiple imputation. Specifically, it examines the influence of sample size, missing rates, missingness mechanism combinations, missingness types (linear or convex), and the absence or presence…
Descriptors: Monte Carlo Methods, Research Methodology, Test Validity, Factor Analysis
Cheung, Shu Fai; Chan, Darius K.-S. – Educational and Psychological Measurement, 2008
In meta-analysis, it is common to have dependent effect sizes, such as several effect sizes from the same sample but measured at different times. Cheung and Chan proposed the adjusted-individual and adjusted-weighted procedures to estimate the degree of dependence and incorporate this estimate in the meta-analysis. The present study extends the…
Descriptors: Effect Size, Academic Achievement, Meta Analysis, Correlation
Zientek, Linda Reichwein; Capraro, Mary Margaret; Capraro, Robert M. – Educational Researcher, 2008
The authors of this article examine the analytic and reporting features of research articles cited in "Studying Teacher Education: The Report of the AERA Panel on Research and Teacher Education" (Cochran-Smith & Zeichner, 2005b) that used quantitative reporting practices. Their purpose was to help to identify reporting practices that can be…
Descriptors: Preservice Teacher Education, Social Science Research, Intervals, Social Sciences

Kaplan, David – Journal of Educational and Behavioral Statistics, 1995
This article considers the impact of missing data arising from balanced incomplete block (BIB) spiraled designs on the chi-square goodness-of-fit test in factor analysis. The new approach is shown to outperform the pairwise available case method for continuous variables and to be comparatively better for dichotomous variables. (SLD)
Descriptors: Chi Square, Factor Analysis, Goodness of Fit, Monte Carlo Methods

Wilson, Gale A.; Martin, Samuel A. – Educational and Psychological Measurement, 1983
Either Bartlett's chi-square test of sphericity or Steiger's chi-square test can be used to test the significance of a correlation matrix to determine the appropriateness of factor analysis. They were evaluated using computer-generated correlation matrices. Steiger's test is recommended due to its increased power and computational simplicity.…
Descriptors: Comparative Analysis, Correlation, Factor Analysis, Hypothesis Testing

Glorfeld, Louis W. – Educational and Psychological Measurement, 1995
A modification of Horn's parallel analysis is introduced that is based on the Monte Carlo simulation of the null distributions of the eigenvalues generated from a population correlation identity matrix. This modification reduces the tendency of the parallel analysis procedure to overextract or to extract poorly defined factors. (SLD)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
Rocci, Roberto; Vichi, Maurizio – Psychometrika, 2005
A new methodology is proposed for the simultaneous reduction of units, variables, and occasions of a three-mode data set. Units are partitioned into a reduced number of classes, while, simultaneously, components for variables and occasions accounting for the largest common information for the classification are identified. The model is a…
Descriptors: Factor Analysis, Classification, Least Squares Statistics, Monte Carlo Methods
Tucker, Ledyard R.; And Others – 1986
A Monte Carlo study of five indices of dimensionality of binary items used a computer model that allowed sampling of both items and people. Five parameters were systematically varied in a factorial design: (1) number of common factors from one to five; (2) number of items, including 20, 30, 40, and 60; (3) sample sizes of 125 and 500; (4) nearly…
Descriptors: Correlation, Difficulty Level, Educational Research, Expectancy Tables
Stricker, Lawrence J; And Others – 1972
This study's aim was to assess the validity of naive subjects' implicit personality theories, the correspondence among the theories, and the influence of social desirability on them. High school girls classified the items from the MMPI Psychopathic Deviate scale into clusters representing different traits. These clusters agreed closely with the…
Descriptors: Factor Analysis, Females, High School Seniors, High School Students