New Effect Size Measures for Structural Equation Modeling

Gomer, Brenna; Jiang, Ge; Yuan, Ke‐Hai

doi:10.1080/10705511.2018.1545231

Cited by 14 publications

(14 citation statements)

References 32 publications

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“…The required sample to conduct a structural model for a given number of latent and observed variables, expected effect size, and desired statistical power is calculated using a web-based calculator by Soper (2019). With 14 latent and 9 observed variables, a medium effect size of 0.3 (Gomer et al, 2018), desired statistical power of 0.8 (Cohen, 1988;Westland, 2010), and 0.05 level of significance the recommended minimum sample to detect an effect in the present structural model is 208. Therefore, according to statistical recommendations the present sample size of 466 falls within the limits of a moderate effect size.…”

Section: Data Analysis and Resultsmentioning

confidence: 99%

Fashion brands are engaging the millennials: a moderated-mediation model of customer-brand engagement, participation, and involvement

Nagaraj

Katkam

2019

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Purpose Millennial generation is fashion inclined, interactive and informative social beings. They are very conscious of the brands they wear. Millennia seek, share, inform and exchange fashion brand-related information on social networking sites (SNS). Marketers are subsequently engaging the young prospects and customers to keep up or improve enthusiasm and participation. The study attempts to investigate the role of customer-brand engagement (CBE) of millennials with fashion brands on SNS. The study simultaneously tests the moderating role of involvement levels affecting participation and CBE leading to brand loyalty. Design/methodology/approach The study followed a purposive sample by collecting 466 respondents from the graduate students of a university. The study adopted structural equation modelling (SEM) and Hayes process macros in SPSS 20.0 to test the moderated-mediation model. Findings The study confirms the mediating role of CBE in the relationship between participation and brand loyalty. Different degrees of involvement moderate the mediating role of CBE. Higher levels of involvement enhance the positive effect of participation on CBE. Originality/value The study is first of its kind to investigate the role of CBE and involvement among the millennial group. It also contributes to the related theories like service-dominant logic, social exchange theory and consumer culture theory regarding a unique population group, which is promising and profitable.

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Section: Data Analysis and Resultsmentioning

confidence: 99%

Fashion brands are engaging the millennials: a moderated-mediation model of customer-brand engagement, participation, and involvement

Nagaraj

Katkam

2019

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“…As noted by Ropovik (2015), “a significant chi-square does not necessarily imply a useless model” and fit indices can assist in differentiating between a model that retains some merit despite misspecifications and a model that is grossly incorrect and should be discarded (Millsap, 2007). However, over time, fit indices have migrated into being used as binary arbiters of fit and function as ad hoc hypothesis tests—much like the χ 2 test—rather than a supplement to quantify the magnitude of misfit (Gomer et al, 2019, p. 372).…”

Section: Fit Indices As a Continuum Not An Ad Hoc Hypothesis Testmentioning

confidence: 99%

Dynamic fit index cutoffs for confirmatory factor analysis models.

McNeish¹,

Wolf²

2023

Psychological Methods

184

145

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Model fit assessment is a central component of evaluating confirmatory factor analysis models and often the validity of psychological assessments. Fit indices remain popular and researchers often judge fit with fixed cutoffs derived by Hu and Bentler (1999). Despite their overwhelming popularity, methodological studies have cautioned against fixed cutoffs, noting that the meaning of fit indices varies based on a complex interaction of model characteristics like factor reliability, number of items, and number of factors. Criticism of fixed cutoffs stems primarily from the fact that they were derived from one specific confirmatory factor analysis model and lack generalizability. To address this, we propose a simulation-based method called dynamic fit index cutoffs such that derivation of cutoffs is adaptively tailored to the specific model and data characteristics being evaluated. Unlike previously proposed simulation-based techniques, our method removes existing barriers to implementation by providing an open-source, web-based Shiny software application that automates the entire process so that users neither need to manually write any software code nor be knowledgeable about foundations of Monte Carlo simulation. Additionally, we extend fit index cutoff derivations to include sets of cutoffs for multiple levels of misspecification. In doing so, fit indices can more closely resemble their originally intended purpose as effect sizes quantifying misfit rather than improperly functioning as ad hoc hypothesis tests. We also provide an approach specifically designed for the nuances of one-factor models, which have received surprisingly little attention in the literature despite frequent substantive interests in unidimensionality.

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“…Authors such as Hair et al (2018) and Kline (2016) considered that a sample size greater than 250 is sufficient in CB-SEM to minimize the impact of sampling error. In this sense, the sample of the present study is considered adequate to carry out the analysis and verify the research hypotheses (Gomer et al, 2019).…”

Section: H5mentioning

confidence: 99%

Entrepreneurial Leadership, Work Engagement, and Innovative Work Behavior: The Moderating Role of Gender

Pinela¹,

Guevara²,

Armijos³

2022

IJEBA

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Purpose: This research examines the effect of entrepreneurial leadership on innovative work behavior and the mediation of work engagement in that relationship. Additionally, it evaluates the moderation of gender in this relationship. Design/Methodology/Approach: We use data from medium-sized companies in Guayaquil and Quito in Ecuador. Through the use of a structural equation model, we analyze the mediating effect of work engagement in the relationship between entrepreneurial leadership and innovative behavior and the moderating role of gender. Findings: The results show that entrepreneurial leadership has a significant positive impact on innovative behavior. Likewise, we find evidence for a significant mediation effect of work engagement in the relationship between entrepreneurial leadership and innovative work behavior. Additionally, gender moderation is verified, showing that the impact of entrepreneurial leadership on innovative behavior is stronger in women than in men. Originality/value: This study proposes a new model considering three constructsentrepreneurial leadership, work engagement, and innovative work behavior-which will serve future research on these topics. With these findings, we contribute new knowledge to both the scientific community and the management of firms.

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New Effect Size Measures for Structural Equation Modeling

Cited by 14 publications

References 32 publications

Fashion brands are engaging the millennials: a moderated-mediation model of customer-brand engagement, participation, and involvement

Fashion brands are engaging the millennials: a moderated-mediation model of customer-brand engagement, participation, and involvement

Dynamic fit index cutoffs for confirmatory factor analysis models.

Entrepreneurial Leadership, Work Engagement, and Innovative Work Behavior: The Moderating Role of Gender

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