2014
DOI: 10.1111/jedm.12050
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Hayes, Andrew F. (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression‐Based Approach. New York, NY: The Guilford Press

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Cited by 939 publications
(444 citation statements)
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“…Moreover, Pearson correlation was conducted to explore the association between key study variables, including chronotype, BMI, and caffeinated drinks consumption. To identify the mediating effect of caffeinated drinks consumption and physical state on the association between chronotype and BMI, we employed the mediation model and bootstrap technique using SPSS PROCESS and Amos 21, respectively [31]. In addition, a total of three sociological variables or medical characteristics, namely, age, gender, and psychological distress total scores, were controlled in the model.…”
Section: Methodsmentioning
confidence: 99%
“…Moreover, Pearson correlation was conducted to explore the association between key study variables, including chronotype, BMI, and caffeinated drinks consumption. To identify the mediating effect of caffeinated drinks consumption and physical state on the association between chronotype and BMI, we employed the mediation model and bootstrap technique using SPSS PROCESS and Amos 21, respectively [31]. In addition, a total of three sociological variables or medical characteristics, namely, age, gender, and psychological distress total scores, were controlled in the model.…”
Section: Methodsmentioning
confidence: 99%
“…To test this possibility we conducted mediation analyses using the bootstrapping methods delineated by Preacher and Hayes (2004) and utilizing Hayes' PROCESS Model (Hayes, 2013;Preacher & Hayes, 2004). Each analysis was performed using 10,000 bootstrap resamples to estimate the indirect effect of the proposed mediator variables.…”
Section: Mediation Of the Relationship Between Technology Engagementmentioning
confidence: 99%
“…The assumptions of multiple regression were met, and the steps for moderation were conducted as per Hayes [35] PROCESS Model 1. As shown in table 2, the interaction term was significant, and the change in the model with the addition of the interaction term was significant.…”
Section: Resultsmentioning
confidence: 99%
“…Mediation analyses were conducted as per Hayes [35] PROCESS Model 8. Based on 1,000 bootstrapped samples using bias-corrected and accelerated 95% confidence intervals, after controlling for the effect of depression (p > 0.05), the interaction variable did not significantly predict OCD beliefs (p > 0.05).…”
Section: Resultsmentioning
confidence: 99%