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Journal ArticleDOI

Significance tests and goodness of fit in the analysis of covariance structures

Peter M. Bentler, +1 more
- 01 Nov 1980 - 
- Vol. 88, Iss: 3, pp 588-606
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TLDR
In this article, a general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models, and the importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models.
Abstract
Factor analysis, path analysis, structural equation modeling, and related multivariate statistical methods are based on maximum likelihood or generalized least squares estimation developed for covariance structure models. Large-sample theory provides a chi-square goodness-of-fit test for comparing a model against a general alternative model based on correlated variables. This model comparison is insufficient for model evaluation: In large samples virtually any model tends to be rejected as inadequate, and in small samples various competing models, if evaluated, might be equally acceptable. A general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models. Use of the null model in the context of a procedure that sequentially evaluates the statistical necessity of various sets of parameters places statistical methods in covariance structure analysis into a more complete framework. The concepts of ideal models and pseudo chi-square tests are introduced, and their roles in hypothesis testing are developed. The importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models is also emphasized. Normed and nonnormed fit indices are developed and illustrated.

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Strategic Determinants of Service Quality and Performance: Evidence from the Banking Industry

TL;DR: In this article, the authors focus on an important new service management strategy: the operations capabilities-service quality-performance C-SQ-P triad triad, and explore three related questions: What generic operations capabilities are among the strategic determinants of service quality? Does service quality affect market performance? How is market conduct related to the C-sq-p triad?
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Self-reported psychopathy: a validation study.

TL;DR: Two studies are reported examining the reliability and validity of Levenson's Self-Report Psychopathy Scale (LSRP) in a noninstitutionalized population and psychopathic undergraduates showed deficits in response modulation similar to those observed in incarcerated psychopaths.
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Plans are nothing, changing plans is everything: the impact of changes on project success

TL;DR: Based on a sample of 448 projects, the interactions between three project planning variables, the quality of planning, goal changes, plan-changes and project success are analyzed and the results clearly show that the positive total effect of thequality of planning is almost completely overridden by the negative effect of goal changes.
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Understanding and measuring entrepreneurial leadership style.

TL;DR: Although entrepreneurial leadership is embraced in the popular press and in classrooms, academic knowledge remains underdeveloped as mentioned in this paper, and the construct of entrepreneurial leadership has not yet been developed in the academic domain.
References
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Journal ArticleDOI

A reliability coefficient for maximum likelihood factor analysis

TL;DR: In this paper, a reliability coefficient is proposed to indicate quality of representation of interrelations among attributes in a battery by a maximum likelihood factor analysis, which can indicate that an otherwise acceptable factor model does not exactly represent the interrelations between the attributes for a population.
Journal ArticleDOI

A general approach to confirmatory maximum likelihood factor analysis

Karl G. Jöreskog
- 01 Jun 1969 - 
TL;DR: In this paper, the authors describe a general procedure by which any number of parameters of the factor analytic model can be held fixed at any values and the remaining free parameters estimated by the maximum likelihood method.
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