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Showing all 14 results Save | Export
Kush, Joseph M.; Konold, Timothy R.; Bradshaw, Catherine P. – Grantee Submission, 2021
Multilevel structural equation (MSEM) models allow researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This paper…
Descriptors: Sampling, Structural Equation Models, Factor Structure, Monte Carlo Methods
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Soto, Christian; Gutierrez de Blume, Antonio P.; Asún, Rodrigo; Jacovina, Matthew; Vásquez, Claudio – Frontline Learning Research, 2018
The purpose of this research endeavor was to develop and validate a new measurement tool predicated on previous research to assess learners' metacomprehension during reading. In two separate studies with Chilean undergraduate students (N = 923), we demonstrate the versatility and utility of our proposed Metacomprehension Inventory (MI). In Study…
Descriptors: Undergraduate Students, Foreign Countries, Factor Structure, Correlation
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Ersanli, Ercümend; Mameghani, Shiva Saeighi – Journal of Education and Practice, 2016
In the present study, the Tolerance Scale developed by Ersanli (2014) was adapted to the Iranian culture, and its validity and reliability were investigated in the case of Iranian college students. The participants consisted of 552 Iranian college students (62% male, M = 20.84, S.D.: 1.53) selected using the convenience sampling method. The sample…
Descriptors: Foreign Countries, College Students, Construct Validity, Reliability
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Ruscio, John; Roche, Brendan – Psychological Assessment, 2012
Exploratory factor analysis (EFA) is used routinely in the development and validation of assessment instruments. One of the most significant challenges when one is performing EFA is determining how many factors to retain. Parallel analysis (PA) is an effective stopping rule that compares the eigenvalues of randomly generated data with those for…
Descriptors: Factor Analysis, Simulation, Sampling, Correlation
Thien, Lei Mee; Razak, Nordin Abd; Jamil, Hazri – Australian Association for Research in Education (NJ1), 2012
The purpose of this study is twofold: (1) to initialize a new conceptualization of positive feature based Friendship Quality (FQUA) scale on the basis of four dimensions: Closeness, Help, Acceptance, and Safety; and (2) to develop and validate FQUA scale in the form of reflective measurement model. The scale development and validation procedures…
Descriptors: Factor Analysis, Safety, Measures (Individuals), Friendship
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Tosun, Ulku; Karadag, Engin – Educational Sciences: Theory and Practice, 2008
The purpose of this study was to adapt the CTI to Turkish and investigate the Turkish version of the CTI . First, the CTI items were translated to Turkish and translation validity of the items were investigated. Second, for the language equivalency of the CTI, 42 ESL teachers from eight different secondary schools in Istanbul were selected as a…
Descriptors: Factor Structure, Factor Analysis, Correlation, Psychometrics
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Katzenmeyer, William G.; Stenner, A. Jackson – Educational and Psychological Measurement, 1975
The problem of demonstrating replicability of factor structure across random variables is addressed. Procedures are outlined which combine the use of random subsample replication strategies with the correlations between factor score estimates across replicate pairs to generate a coefficient of replicability and confidence intervals associated with…
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
Aleamoni, Lawrence M. – 1974
The relationship of sample size to number of variables in the use of factor analysis has been treated by many investigators. In attempting to explore what the minimum sample size should be, none of these investigators pointed out the constraints imposed on the dimensionality of the variables by using a sample size smaller than the number of…
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
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Reid, W. A.; Holley, B. J. – British Journal of Educational Psychology, 1974
A 40 item, Likert type attitude inventory was completed by a sample fo 448 teachers in schools with sixth forms. Implications for policy making in the area of sixth form education are briefly discussed. (Editor)
Descriptors: Correlation, Educational Policy, Educational Psychology, Factor Analysis
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Loo, Robert – Perceptual and Motor Skills, 1983
In examining considerations in determining sample sizes for factor analyses, attention was given to the effects of outliers; the standard error of correlations, and their effect on factor structure; sample heterogeneity; and the misuse of rules of thumb for sample sizes. (Author)
Descriptors: Correlation, Error of Measurement, Evaluation Methods, Factor Analysis
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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
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Zwick, William R.; Velicer, Wayne F. – 1984
A common problem in the behavioral sciences is to determine if a set of observed variables can be more parsimoniously represented by a smaller set of derived variables. To address this problem, the performance of five methods for determining the number of components to retain (Horn's parallel analysis, Velicer's Minimum Average Partial (MAP),…
Descriptors: Behavioral Science Research, Comparative Analysis, Correlation, Data Interpretation
Pennell, Roger – 1971
The problem considered is that of an investigator sampling two or more correlation matrices and desiring to fit a model where a factor pattern matrix is assumed to be identical across samples and we need to estimate only the factor covariance matrix and the unique variance for each sample. A flexible, least squares solution is worked out and…
Descriptors: Analysis of Covariance, Cognitive Tests, Computer Oriented Programs, Correlation
Vasu, Ellen S.; Elmore, Patricia B. – 1975
The effects of the violation of the assumption of normality coupled with the condition of multicollinearity upon the outcome of testing the hypothesis Beta equals zero in the two-predictor regression equation is investigated. A monte carlo approach was utilized in which three differenct distributions were sampled for two sample sizes over…
Descriptors: Correlation, Error of Measurement, Factor Structure, Hypothesis Testing