Statistical power and structural equation models in business research

By S. McQuitty. 2004

411 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/dcdd28d813fd12772cd63d3fb6539acf688fb94e

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In Artificial Intelligence

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Citations in the corpus

Measuring Service Quality in E-Retailing (2006, methodology): “College students were chosen because a recent Jupiter Research (2004) report stated that the young adult population was the most active Web users.”
Effect of Ethical Climate on Turnover Intention: Linking Attitudinal- and Stress Theory (2008, background): “When power is high, the HkeHhood of not rejecting a truly bad model and theory is low (MacCaUum et al., 1996; McQuitty, 2004).”
Evaluating Model Fit:a Synthesis of the Structural Equation Modelling Literature (2008, background): “This is possible due to the known distribution values of the statistic and subsequently allows for the null hypothesis (poor fit) to be tested more precisely (McQuitty, 2004).”
Toward Understanding Remote Workers’ Management of Work–Family Boundaries: The Complexity of Workplace Embeddedness (2017, background): “99) indicates a low likelihood of not rejecting a truly bad model (McQuitty, 2004).”
Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General (2018, methodology): “…statistics, in factor analysis too, it is considered a good practice to a priori determine the minimum sample size required to achieve an acceptable level of statistical power for the factor structure under evaluation (Thomas, 1997; Schumacker & Lomax, 2015; McQuitty, 2004; Singh et al., 2016).”
Structural equation modelling: guidelines for determining model fit (2008, background): “This is possible due to the known distribution values of the statistic and subsequently allows for the null hypothesis (poor fit) to be tested more precisely (McQuitty, 2004).”
Emotional Information Management and Responses to Emotional Appeals (2011, background): “However, with N = 280 and df = 181, the statistical power associated with the RMSEA statistic approaches 1.0 (test of close fit, MacCallum, Browne, and Sugawara 1996), so the goodness-of-fit statistics are assumed conservative (Kaplan 1995; McQuitty 2004).”
Information processing and strategic decision-making in small and medium-sized enterprises: The role of human and social capital in attaining decision effectiveness (2013, methodology): “Low sample size is the most critical concern in using SEM (McQuitty, 2004) and this is certainly not the case in our study, where the sample size is higher than”
A comprehensive model of customer direct and indirect revenge: understanding the effects of perceived greed and customer power (2010, methodology): “It should be noted that simplified covariance-based models have been regularly published in marketing (see McQuitty 2004 ).”