Spss macro process program

Manufactured by IBM

The SPSS macro PROCESS program is a statistical analysis tool developed by Andrew F. Hayes. The program provides a comprehensive set of functions for conducting moderation, mediation, and conditional process analysis. It is designed to work within the IBM SPSS software environment.

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Spss software version 25, by IBM (2 mentions)

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SPSS program (723 citations) PROCESS macro (78 citations) SPSS PROCESS macro (69 citations) SPSS macro (19 citations) SPSS PROCESS (13 citations) SPSSTM (8 citations) PROCESS macro program (2 citations)

4 protocols using spss macro process program

Mediating Effects of Coping Styles on Social Support and Job Satisfaction

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Firstly, descriptive statistics and Pearson’s correlation coefficients were performed for the social support, coping styles, and job satisfaction variables using SPSS 25.0. Secondly, we used multiple mediation analysis with bootstrap estimation (Preacher and Hayes, 2008 (link)) to test the significance of the mediating effects of coping styles (i.e., positive coping styles and negative coping styles) on the relationship between social support and job satisfaction.
In order to compare the strengths of the mediating effects of the different types of coping styles, we used the SPSS macro PROCESS program which was designed by Hayes (2018) . The significance of the mediating effect was accepted if the 95% confidence interval (bias-corrected and accelerated; 5,000 bootstrap samples were specified) did not overlap with zero (Preacher and Hayes, 2008 (link)).

Yang Y., Lu X., Ban Y, & Sun J. (2022). Social Support and Job Satisfaction in Kindergarten Teachers: The Mediating Role of Coping Styles. Frontiers in Psychology, 13, 809272.

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Emotional Intelligence and Subjective Well-Being

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SPSS software (version 25.0) was used for data analysis. We first established the relationships among EI, effort-reward imbalance, emotional regulation strategies (cognitive reappraisal and expressive suppression), and SWB. Then, we used the SPSS macro PROCESS program to evaluate the mediating effect of emotional regulation strategies on EI and SWB and the moderating effect of effort-reward imbalance.

Sha J., Tang T., Shu H., He K, & Shen S. (2022). Emotional Intelligence, Emotional Regulation Strategies, and Subjective Well-Being Among University Teachers: A Moderated Mediation Analysis. Frontiers in Psychology, 12, 811260.

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Depression, ADHD, and Quality of Life

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IBM SPSS-23 program was used for data analysis (SPSS Inc; Chicago, IL, USA). Groups were compared using the independent samples t-test for parametric continuous variables (such as age and psychometric test scores) and the chi-square test for categorical variables (such as marital status, education, and ADHD rates). The relationships between clinical variables and test scores were analyzed using the Pearson correlation coefficients. The bootstrap method of Preacher and Hayes (2008) was used to determine the significance of the mediation effect in the study [32]. SPSS Macro Process program was used to calculate the Bootstrap method. Five thousand preloads were made in the calculation of the intermediary effect. Hayes’ (2013) Model 4 was used to identify the mediating role of ADHD scores in the effect of depression severity on quality of life [33]. Confidence intervals without zero indicate that the mediating effect is significant [32]. We also used the Sobel test to test significance of the mediation effect [34]. Probabilities less than 0.05 were used as the level of statistical significance in the analyzes.

TÜRKOĞLU G, & SELVİ Y. (2021). Attention-deficit hyperactivity disorder symptoms and quality of life in female patients with fibromyalgia. Turkish Journal of Medical Sciences, 51(4), 1747-1755.

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Mediating Role of Social Support in Life Balance

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The data were statistically analyzed using SPSS software (Version 25.0). First, a Pearson correlation analysis was used to test the relationship between the SA, SS, and SQOL of LBC. Second, the SPSS macro PROCESS program was used to test the significance of the mediating effects of SS. Third, AMOS 25.0 was used to construct measurement model and structural equation models (SEM) of the variables and analyze their mediating mechanisms. Finally, the “Model Indirect” command in AMOS was used to calculate the standardized indirect effect parameters using 5,000 replicates of bootstrap analysis to test the significance of indirect effects.
In addition, to improve the rigor of the study, we tested for possible common method bias (Podsakoff et al., 2003 (link)) prior to conducting statistical analysis. We used Harman’s one-factor test to perform an exploratory factor analysis for all items in the scales prior to rotation. The results showed that a total of 21 factors had eigenvalues greater than 1 and that the variance explained by the first factor was only 13.19%, which is much lower than the critical value criterion of 40% (Podsakoff et al., 2003 (link)). Therefore, we can infer that there was no serious common method bias in this study.

Yang Y, & Lu X. (2022). Social Anxiety and Subjective Quality of Life Among Chinese Left-Behind Children: The Mediating Role of Social Support. Frontiers in Psychology, 13, 836461.

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