Journal ArticleDOI
Comparative fit indexes in structural models
TLDR
A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models and two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes.Abstract:
Normed and nonnormed fit indexes are frequently used as adjuncts to chi-square statistics for evaluating the fit of a structural model A drawback of existing indexes is that they estimate no known population parameters A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models Two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes CFI avoids the underestimation of fit often noted in small samples for Bentler and Bonett's (1980) normed fit index (NFI) FI is a linear function of Bentler and Bonett's non-normed fit index (NNFI) that avoids the extreme underestimation and overestimation often found in NNFI Asymptotically, CFI, FI, NFI, and a new index developed by Bollen are equivalent measures of comparative fit, whereas NNFI measures relative fit by comparing noncentrality per degree of freedom All of the indexes are generalized to permit use of Wald and Lagrange multiplier statistics An example illustrates the behavior of these indexes under conditions of correct specification and misspecification The new fit indexes perform very well at all sample sizesread more
Citations
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The Factors Predicting Stress, Anxiety and Depression in the Parents of Children with Autism
TL;DR: Variables assessing parental cognitions and socioeconomic support were found to be more significant predictors of parental mental health problems than child-centric variables.
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Parsimony‐based fit indices for multiple‐indicator models: Do they work?
TL;DR: In this article, a simulation approach is used to investigate a multiple-indicator regression model in the context of covariance structure analysis, which is a commonly used type of model in applications of structure analysis.
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Client‐Acceptance Decisions: Simultaneous Effects of Client Business Risk, Audit Risk, Auditor Business Risk, and Risk Adaptation
TL;DR: In this paper, a model is developed and tested that characterizes the client acceptance decision as a process of risk evaluation and risk adaptation, and the model proposes that auditors will evaluate client-related risks (e.g., financial viability, and internal control) and use that evaluation to determine if the audit firm will suffer a loss on the engagement via a lack of engagement profitability or future litigation.
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The impact of prenatal maternal stress and optimistic disposition on birth outcomes in medically high-risk women.
TL;DR: Examining prospective impact of PNMS and dispositional optimism on birth weight and gestational age in a medically high-risk sample suggests that chronic stress in pregnancy may be a reflection of underlying dispositions that contribute to adverse birth outcomes.
Journal ArticleDOI
Social context, student's motivation, and academic achievement: Toward a process model
TL;DR: In this article, a motivational process model of academic achievement was proposed and tested using two studies using a prospective design, and participants were 1,623 ninth-grade students and 1,098 tenth-graders.
References
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Journal ArticleDOI
Significance tests and goodness of fit in the analysis of covariance structures
TL;DR: 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.
Journal ArticleDOI
A reliability coefficient for maximum likelihood factor analysis
Ledyard R Tucker,Charles Lewis +1 more
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
Model Selection and Akaike's Information Criterion (AIC): The General Theory and Its Analytical Extensions.
TL;DR: In this article, the entropy-based information criterion (AIC) has been extended in two ways without violating Akaike's main principles: CAIC and CAICF, which make AIC asymptotically consistent and penalize overparameterization more stringently.
Journal ArticleDOI
Goodness-of-fit indexes in confirmatory factor analysis : The effect of sample size
TL;DR: In this paper, the influence of sample size on different goodness-of-fit indices used in confirmatory factor analysis (CFA) was examined and the results are consistent with the observation that the amount of random, unexplained variance varies inversely with sample size.