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Bayesian Estimation and Testing of Structural Equation Models
 Psychometrika
, 1999
"... The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameter ..."
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Cited by 37 (10 self)
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The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same as those based on the maximum likelihood solution, e.g., output from LISREL or EQS. In small samples, however, the likelihood surface is not Gaussian and in some cases contains local maxima. Nevertheless, the Gibbs sample comes from the correct posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, the posterior can be used to make inferences about the parameters of underidentified models, as we illustrate on a simple errorsinvariables model.
The Robustness of LISREL Modeling Revisited
 Structural equation modeling: Present and future: A Festschrift in honor of Karl Jöreskog (pp. 139–168). Chicago: Scientific Software International
, 2001
"... Somer obustness questions in str uctur al equation modeling (SEM) ar intr duced. Factor that a#ect the occuruv ce of nonconver gence and impr: er solutions arr/7 ewed in detail. ..."
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Cited by 27 (2 self)
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Somer obustness questions in str uctur al equation modeling (SEM) ar intr duced. Factor that a#ect the occuruv ce of nonconver gence and impr: er solutions arr/7 ewed in detail.
A Factor and Structural Equation Analysis of the Enterprise
 Systems Success Measurement Model. International Conference of Information Systems
, 2004
"... Enterprise systems entail complex organizational interventions. Accurately gauging the impact of any complex information system requires understanding its multidimensionality, and the development of a correspondent, standardized, validated, and robust measurement instrument. Despite the popularity a ..."
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Cited by 22 (5 self)
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Enterprise systems entail complex organizational interventions. Accurately gauging the impact of any complex information system requires understanding its multidimensionality, and the development of a correspondent, standardized, validated, and robust measurement instrument. Despite the popularity and potential of enterprise systems in modern organizations, no acceptably valid and reliable enterprise system success assessment scale has heretofore been developed. The present study tests the reliability and construct validity of the enterprise system success (ESS) measurement model and variants against new empirical data. Results from a confirmatory factor analysis utilizing structural equation modeling techniques confirm the existence of four distinct and individually important dimensions of ESS: individual impact, organizational impact, system quality, and information quality. Based on the analysis of results, the ESS instrument demonstrates strong reliability and validity.
The TETRAD Project: Constraint Based Aids to Causal Model Specification
 MULTIVARIATE BEHAVIORAL RESEARCH
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The structure of negative symptoms within schizophrenia: implications for assessment
 Schizophr. Bull
, 2006
"... This review examines the structural validity of negative symptoms focusing on 2 questions: (1) Do negative symptoms represent a domain separate from other symptoms in schizophrenia? and (2) Within negative symptoms, is there a structure that suggests multidimensionality? Results from exploratory and ..."
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Cited by 12 (0 self)
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This review examines the structural validity of negative symptoms focusing on 2 questions: (1) Do negative symptoms represent a domain separate from other symptoms in schizophrenia? and (2) Within negative symptoms, is there a structure that suggests multidimensionality? Results from exploratory and confirmatory factor analytic studies are examined to address these questions. Across studies and symptom instruments, negative symptoms appear to consistently emerge as a factor separate from other dimensions of the illness in schizophrenia. Whether 2, 3, or 5factor models are identified, negative symptoms consistently load on a factor separate from positive symptoms, affective symptoms of depression or anxiety, and symptoms of disorganization. Focusing on negative symptoms themselves, factor analytic findings suggest that this construct is multidimensional with at least 2 factors (involving diminished expression and anhedoniaasociality). Although these factors were replicable, serious limitations were noted in this literature. Thus, 2 (or even 3 or 5) factor models of negative symptoms should not be considered definitive, but rather all converge to support the general conclusion of the multidimensionality of negative symptoms. The later findings indicate the importance of employing assessments that provide adequate coverage of the broad domain of negative symptoms. Importantly, caution is noted in the interpretability of findings based on existing instruments, and implications for future assessment are discussed. Key words: negative symptoms/factor analysis/
Latent variable models under misspecification
 Two Stage Least Squares (2SLS) and Maximum Likelihood (ML) estimators. Sociological Methods and Research
, 2007
"... This article compares maximum likelihood (ML) estimation to three variants of twostage least squares (2SLS) estimation in structural equation models. The authors use models that are both correctly and incorrectly specified. Simulated data are used to assess bias, efficiency, and accuracy of hypot ..."
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Cited by 8 (2 self)
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This article compares maximum likelihood (ML) estimation to three variants of twostage least squares (2SLS) estimation in structural equation models. The authors use models that are both correctly and incorrectly specified. Simulated data are used to assess bias, efficiency, and accuracy of hypothesis tests. Generally, 2SLS with reduced sets of instrumental variables performs similarly to ML when models are correctly specified. Under correct specification, both estimators have little bias except at the smallest sample sizes and are approximately equally efficient. As predicted, when models are incorrectly specified, 2SLS generally performs better, with less bias and more accurate hypothesis tests. Unless a researcher has tremendous confidence in the correctness of his or her model, these results suggest that a 2SLS estimator should be considered.
The modelsize effect on traditional and modified tests of covariance structures
 Structural Equation Modeling
, 2007
"... According to Kenny and McCoach (2003), chisquare tests of structural equation models produce inflated Type I error rates when the degrees of freedom increase. So far, the amount of this bias in large models has not been quantified. In a Monte Carlo study of confirmatory factor models with a range o ..."
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Cited by 5 (4 self)
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According to Kenny and McCoach (2003), chisquare tests of structural equation models produce inflated Type I error rates when the degrees of freedom increase. So far, the amount of this bias in large models has not been quantified. In a Monte Carlo study of confirmatory factor models with a range of 48 to 960 degrees of freedom it was found that the traditional maximum likelihood ratio statistic, TML, overestimates nominal Type I error rates up to 70 % under conditions of multivariate normality. Some alternative statistics for the correction of modelsize effects were also investigated: the scaled Satorra–Bentler statistic, TSC; the adjusted Satorra–
The Bumpus house sparrow data: a reanalysis using structural equation models
 Evol. Ecol
, 1996
"... We analysed the data of H.C. Bumpus on the survival of house sparrows (Passer domesticus) using structural equation modelling techniques. Using data on seven morphological variables measured by Bumpus, we tested and confirmed a threefactor model that characterized physical attributes for general si ..."
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We analysed the data of H.C. Bumpus on the survival of house sparrows (Passer domesticus) using structural equation modelling techniques. Using data on seven morphological variables measured by Bumpus, we tested and confirmed a threefactor model that characterized physical attributes for general size, leg size and head size. Although males were physically larger than females, we found no difference between males and females in the physical attributes as measured by the three factors. Survival increased significantly with increasing general size and was unrelated to leg size and head size. Wing length, independent of its relationship to the general size factor, was also significantly related to survival. Higher survival was found among birds with short wings. Males had a higher survival compared to females. Their higher survival was mediated, to a lesser extent indirectly, through greater size and, to a greater extent directly, through effects of unknown origin. We favour the use of structural equation modelling methods in studies of selection because of their ability to test and confirm or disconfirm hypotheses related to selection events.
AN ALTERNATE APPROACH TO ASSESSING CROSSCULTURAL MEASUREMENT EQUIVALENCE IN ADVERTISING RESEARCH
"... ABSTRACT: This paper offers a new methodological framework to guide researchers attempting to quantitatively assess how a pluralistic audience perceives a standardized television advertisement. Rasch (1960) measurement theory is introduced as an alternative to the more commonly employed multigroup c ..."
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ABSTRACT: This paper offers a new methodological framework to guide researchers attempting to quantitatively assess how a pluralistic audience perceives a standardized television advertisement. Rasch (1960) measurement theory is introduced as an alternative to the more commonly employed multigroup confirmatory factor analysis (CFA) approach to assessing crosscultural scalar equivalence. By analyzing a multicultural data set, we are able to make various inferences concerning the scalar equivalence of Schlinger’s confusion scale. The methodology reveals the limits of the scale, which in all probability would not have been detected using traditional approaches. For researchers attempting to develop new scales, or even to refine existing scales, strict adherence to established guidelines of item generation together with the application of the proposed methodology should ensure better results for both theorists and practitioners. There is considerable evidence to suggest that attitude toward the advertisement (A ad) influences brand attitudes in pretest situations and in understanding, predicting, and perhaps even forestalling wearout (Lutz 1985). In this regard, reaction profiles have been found to predict A ad both directly (Burke and Edell 1982) and indirectly via ad perceptions (Lutz 1985). Reaction profiles yield more easily quantifiable data and are therefore
The performance of crossvalidation indices used to select among competing covariance structure models under multivariate nonnormality conditions
 Multivariate Behavioral Research
, 2006
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