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Culpepper, Steven Andrew; Aguinis, Herman – Psychological Methods, 2011
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but…
Descriptors: Statistical Analysis, Error of Measurement, Monte Carlo Methods, Structural Equation Models
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Pan, Tianshu; Yin, Yue – Psychological Methods, 2012
In the discussion of mean square difference (MSD) and standard error of measurement (SEM), Barchard (2012) concluded that the MSD between 2 sets of test scores is greater than 2(SEM)[superscript 2] and SEM underestimates the score difference between 2 tests when the 2 tests are not parallel. This conclusion has limitations for 2 reasons. First,…
Descriptors: Error of Measurement, Geometric Concepts, Tests, Structural Equation Models
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Savalei, Victoria – Psychological Methods, 2010
Maximum likelihood is the most common estimation method in structural equation modeling. Standard errors for maximum likelihood estimates are obtained from the associated information matrix, which can be estimated from the sample using either expected or observed information. It is known that, with complete data, estimates based on observed or…
Descriptors: Structural Equation Models, Computation, Error of Measurement, Data
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Harring, Jeffrey R.; Weiss, Brandi A.; Hsu, Jui-Chen – Psychological Methods, 2012
Two Monte Carlo simulations were performed to compare methods for estimating and testing hypotheses of quadratic effects in latent variable regression models. The methods considered in the current study were (a) a 2-stage moderated regression approach using latent variable scores, (b) an unconstrained product indicator approach, (c) a latent…
Descriptors: Structural Equation Models, Geometric Concepts, Computation, Comparative Analysis
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Savalei, Victoria; Kolenikov, Stanislav – Psychological Methods, 2008
Recently, R. D. Stoel, F. G. Garre, C. Dolan, and G. van den Wittenboer (2006) reviewed approaches for obtaining reference mixture distributions for difference tests when a parameter is on the boundary. The authors of the present study argue that this methodology is incomplete without a discussion of when the mixtures are needed and show that they…
Descriptors: Structural Equation Models, Goodness of Fit, Evaluation Methods, Statistical Analysis
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Eid, Michael; Nussbeck, Fridtjof W.; Geiser, Christian; Cole, David A.; Gollwitzer, Mario; Lischetzke, Tanja – Psychological Methods, 2008
The question as to which structural equation model should be selected when multitrait-multimethod (MTMM) data are analyzed is of interest to many researchers. In the past, attempts to find a well-fitting model have often been data-driven and highly arbitrary. In the present article, the authors argue that the measurement design (type of methods…
Descriptors: Structural Equation Models, Multitrait Multimethod Techniques, Statistical Analysis, Error of Measurement
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Bollen, Kenneth A. – Psychological Methods, 2007
R. D. Howell, E. Breivik, and J. B. Wilcox (2007) have argued that causal (formative) indicators are inherently subject to interpretational confounding. That is, they have argued that using causal (formative) indicators leads the empirical meaning of a latent variable to be other than that assigned to it by a researcher. Their critique of causal…
Descriptors: Researchers, Structural Equation Models, Formative Evaluation, Transformative Learning
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Graham, John W.; Taylor, Bonnie J.; Olchowski, Allison E.; Cumsille, Patricio E. – Psychological Methods, 2006
The authors describe 2 efficiency (planned missing data) designs for measurement: the 3-form design and the 2-method measurement design. The 3-form design, a kind of matrix sampling, allows researchers to leverage limited resources to collect data for 33% more survey questions than can be answered by any 1 respondent. Power tables for estimating…
Descriptors: Cost Effectiveness, Structural Equation Models, Psychological Studies, Data Collection
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Woody, Erik; Sadler, Pamela – Psychological Methods, 2005
Structural equation modeling (SEM) offers a flexible method for studying the patterns of interdependence in partners' behavior, which lie at the heart of interactions and relationships. Although SEM has been applied to the study of distinguishable dyads, in which partners are distinguishable by type, such as male and female, it has rarely been…
Descriptors: Structural Equation Models, Females, Males, Interpersonal Relationship