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Raykov, Tenko; Marcoulides, George A. – Measurement: Interdisciplinary Research and Perspectives, 2023
This article outlines a readily applicable procedure for point and interval estimation of the population discrepancy between reliability and the popular Cronbach's coefficient alpha for unidimensional multi-component measuring instruments with uncorrelated errors, which are widely used in behavioral and social research. The method is developed…
Descriptors: Measurement, Test Reliability, Measurement Techniques, Error of Measurement
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Raykov, Tenko; Marcoulides, George A.; Akaeze, Hope O. – Educational and Psychological Measurement, 2017
This note is concerned with examining the relationship between within-group and between-group variances in two-level nested designs. A latent variable modeling approach is outlined that permits point and interval estimation of their ratio and allows their comparison in a multilevel study. The procedure can also be used to test various hypotheses…
Descriptors: Comparative Analysis, Models, Statistical Analysis, Hierarchical Linear Modeling
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Raykov, Tenko; Marcoulides, George A. – Educational and Psychological Measurement, 2015
A direct approach to point and interval estimation of Cronbach's coefficient alpha for multiple component measuring instruments is outlined. The procedure is based on a latent variable modeling application with widely circulated software. As a by-product, using sample data the method permits ascertaining whether the population discrepancy…
Descriptors: Computation, Statistical Analysis, Reliability, Models
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Raykov, Tenko; Dimitrov, Dimiter M.; von Eye, Alexander; Marcoulides, George A. – Educational and Psychological Measurement, 2013
A latent variable modeling method for evaluation of interrater agreement is outlined. The procedure is useful for point and interval estimation of the degree of agreement among a given set of judges evaluating a group of targets. In addition, the approach allows one to test for identity in underlying thresholds across raters as well as to identify…
Descriptors: Interrater Reliability, Models, Statistical Analysis, Computation
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Raykov, Tenko; Marcoulides, George A. – Educational and Psychological Measurement, 2014
This research note contributes to the discussion of methods that can be used to identify useful auxiliary variables for analyses of incomplete data sets. A latent variable approach is discussed, which is helpful in finding auxiliary variables with the property that if included in subsequent maximum likelihood analyses they may enhance considerably…
Descriptors: Data Analysis, Identification, Maximum Likelihood Statistics, Statistical Analysis
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Raykov, Tenko; Pohl, Steffi – Educational and Psychological Measurement, 2013
A method for examining common factor variance in multiple-component measuring instruments is outlined. The procedure is based on an application of the latent variable modeling methodology and is concerned with evaluating observed variance explained by a global factor and by one or more additional component-specific factors. The approach furnishes…
Descriptors: Statistical Analysis, Factor Structure, Scores, Models
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Raykov, Tenko; Pohl, Steffi – Educational and Psychological Measurement, 2013
A procedure for examining essential unidimensionality in multicomponent measuring instruments is discussed. The method is based on an application of latent variable modeling and is concerned with the extent to which a common factor for all components of a given scale accounts for their correlations. The approach provides point and interval…
Descriptors: Measures (Individuals), Statistical Analysis, Factor Structure, Correlation
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Raykov, Tenko – Educational and Psychological Measurement, 2012
A latent variable modeling approach that permits estimation of propensity scores in observational studies containing fallible independent variables is outlined, with subsequent examination of treatment effect. When at least one covariate is measured with error, it is indicated that the conventional propensity score need not possess the desirable…
Descriptors: Computation, Probability, Error of Measurement, Observation
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Raykov, Tenko; Dimitrov, Dimiter M.; Asparouhov, Tihomir – Structural Equation Modeling: A Multidisciplinary Journal, 2010
A method for interval estimation of scale reliability with discrete data is outlined. The approach is applicable with multi-item instruments consisting of binary measures, and is developed within the latent variable modeling methodology. The procedure is useful for evaluation of consistency of single measures and of sum scores from item sets…
Descriptors: Reliability, Computation, Models, Intervals
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Raykov, Tenko – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…
Descriptors: Correlation, Models, Vertical Organization, Predictor Variables
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Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
A latent variable modeling approach for examining population similarities and differences in observed variable relationship and mean indexes in incomplete data sets is discussed. The method is based on the full information maximum likelihood procedure of model fitting and parameter estimation. The procedure can be employed to test group identities…
Descriptors: Models, Comparative Analysis, Groups, Maximum Likelihood Statistics
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Raykov, Tenko – Multivariate Behavioral Research, 2007
A method for point and interval estimation of change in criterion validity of multiple-component measuring instruments as a result of revision is outlined. The procedure is developed within the framework of covariance structure modeling, which complements earlier methods for testing change in composite reliability due to addition or deletion of…
Descriptors: Predictive Validity, Computation, Models, Reliability