2019
DOI: 10.20982/tqmp.15.1.p038
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Path analysis in Mplus: A tutorial using a conceptual model of psychological and behavioral antecedents of bulimic symptoms in young adults

Abstract: Path analysis is a widely used multivariate technique to construct conceptual models of psychological, cognitive, and behavioral phenomena. Although causation cannot be inferred by using this technique, researchers utilize path analysis to portray possible causal linkages between observable constructs in order to better understand the processes and mechanisms behind a given phenomenon. The objectives of this tutorial are to provide an overview of path analysis, step-bystep instructions for conducting path anal… Show more

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Cited by 57 publications
(40 citation statements)
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“…Path analysis, a subcategory of Structural Equation Modeling (SEM), is an extension of multiple regression in that it allows researchers to infer and test a sequence of causal associations between several variables. 55 In other words, path analyses help researchers better understand the processes and mechanisms underlying a given phenomenon. More precisely, Preacher and Hayes 54 method allowed us to determine whether the association between the potential stressors during confinement and job performance was mediated by workers’ increased stress (see hypothesis).…”
Section: Methodsmentioning
confidence: 99%
“…Path analysis, a subcategory of Structural Equation Modeling (SEM), is an extension of multiple regression in that it allows researchers to infer and test a sequence of causal associations between several variables. 55 In other words, path analyses help researchers better understand the processes and mechanisms underlying a given phenomenon. More precisely, Preacher and Hayes 54 method allowed us to determine whether the association between the potential stressors during confinement and job performance was mediated by workers’ increased stress (see hypothesis).…”
Section: Methodsmentioning
confidence: 99%
“…The maximum likelihood estimation method for analysis was used. Bias-corrected bootstrapping techniques (i.e., 1000 samples) were used to estimate the confidence intervals of the indirect effects, in which mediation is inferred if the confidence interval does not include 0 [ 72 ]. Specifically, we conducted bias-corrected bootstrapped 95% confidence interval estimates for the indirect effect of attachment anxiety on intuitive eating through self-compassion, and for the indirect effect of attachment avoidance on intuitive eating through self-compassion.…”
Section: Methodsmentioning
confidence: 99%
“…The data are cross-sectional, and, therefore, our findings do not elucidate a causal relationship. Although many authors use “causal” language in the case of path analysis, causal relationships cannot be achieved through statistical analyses, but only through study designs such as experimental manipulation [ 80 ]. Another limitation of this study is related to pain assessment.…”
Section: Discussionmentioning
confidence: 99%