Mediation, Moderation, and Conditional Process Analysis: Concepts, Computations, and Some Common Confusions

2021 ◽  
Vol 24 ◽  
Author(s):  
Juan-José Igartua ◽  
Andrew F. Hayes
Keyword(s):  
Direct Effect ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Process Analysis ◽  
Psychological Research ◽  
Regression Coefficients ◽  
Conditional Effect ◽  
Using Data ◽  
Conditional Process Analysis ◽  
Mediation Moderation

Abstract This work provides a conceptual introduction to mediation, moderation, and conditional process analysis in psychological research. We discuss the concepts of direct effect, indirect effect, total effect, conditional effect, conditional direct effect, conditional indirect effect, and the index of moderated mediation index, while providing our perspective on certain analysis and interpretation confusions that sometimes arise in practice in this journal and elsewhere, such as reliance on the causal steps approach and the Sobel test in mediation analysis, misinterpreting the regression coefficients in a model that includes a product of variables, and subgroups mediation analysis rather than conditional process analysis when exploring whether an indirect effect depends on a moderator. We also illustrate how to conduct various analyses that are the focus of this paper with the freely-available PROCESS procedure available for SPSS, SAS, and R, using data from an experimental investigation on the effectiveness of personal or testimonial narrative messages in improving intergroup attitudes.

scholarly journals Smartphone Addiction, Narcissism and Aggression: A Mediation Analysis Method

2019 ◽  
Author(s):  
Anjelica Simsek ◽  
Cahit Nuri ◽  
Cemaliye Direktor ◽  
Ahmet Arnavut
Keyword(s):  
Direct Effect ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Total Effect ◽  
Mediation Effect ◽  
Smartphone Addiction ◽  
Analysis Method ◽  
Variable Effect ◽  
Independent Variable ◽  
Mediator Variable

<p>At this study, meditation effect of aggression was analyzed using Baron and Kenny’s mediation analysis method. Baron and Kenny (1986) indicates that to analyze the effect of mediator variable 3 criteria have to be actualized:</p> <p>1. Independent variable have a significant effect on a mediator variable (way a)</p> <p>2. Mediator variable have a significant effect on a dependent variable (way b)</p> <p>3. Independent variable have a significant effect on a dependent variable (way c)</p> <p>PROCESS program were used the meditational effect, it is an extra macro that is downloading to the Daniel and Hayes’s (2016) SPSS program. In this program mediation effect could be evaluated as; total effect, direct effect and indirect effect scores of mediation variable effect on dependent variable (Preacher & Hayes, 2008).</p>

Introduction to Simple Mediation Analysis in SPSS

2015 ◽  
Vol 7 (1) ◽  
pp. 62 ◽  
Author(s):  
Nitika Sharma
Keyword(s):  
Causal Relationship ◽  
Direct Effect ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Indirect Effects ◽  
Regression Analyses ◽  
Mediation Model ◽  
Ols Regression ◽  
Mediator Variable

Data is analyzed using Mediation model which focuses on the estimation of the indirect effect of X on Y through an intermedi - ary mediator variable M causally located between X and Y (i.e., a model of the form X ? M ? Y ) 1 , where X is the input variable, Y is output and M is the Mediating Variable. When researchers want to examine that how X variable exert it effects on Y variable which is commonly intervened by one or two variables denoted by M and this variable has a causal relationship between X &amp; Y as per Figure 1 and termed as Simple Mediation Model. In this casual system there is at least one casual antecedent X variable is projected as influencing an outcome Y through a single inter - vening variable M . Such model establishes two pathways which influences Y by direct effect and indirect effect. In direct effect, pathways lead from X to Y without passing M. In indirect effects, a pathway of X to Y is lead through M. There are two conse - quent variables forming two equations and these equations can be estimated by conducting OLS regression analyses using SPSS or by using PROCESS.sps in SPSS by Andrew F. Hayes. To add PROCESS by Andrew F. Hayes in SPSS.

scholarly journals Conditional Process Analysis in Two-Instance Repeated-Measures Designs

2019 ◽  
Author(s):  
Amanda Kay Montoya
Keyword(s):  
Mediation Analysis ◽  
Repeated Measures ◽  
Process Analysis ◽  
Repeated Measurements ◽  
Process Models ◽  
Outcome Variable ◽  
Moderation Analysis ◽  
Repeated Measures Design ◽  
Independent Variable ◽  
Conditional Process Analysis

Conditional process models are commonly used in many areas of psychology research as well as research in other academic fi?elds (e.g., marketing, communication, and education). Conditional process models combine mediation analysis and moderation analysis. Mediation analysis, sometimes called process analysis, investigates if an independent variable influences an outcome variable through a specific?c intermediary variable, sometimes called a mediator. Moderation analysis investigates if the relationship between two variables depends on another. Conditional process models are very popular because they allow us to better understand how the processes we are interested in might vary depending on characteristics of different individuals, situations, and other moderating variables. Methodological developments in conditional process analysis have primarily focused on the analysis of data collected using between-subjects experimental designs or cross-sectional designs. However, another very common design is the two-instance repeated-measures design. A two-instance repeated-measures design is one where each subject is measured twice; once in each of two instances. In the analysis discussed in this dissertation, the factor that differentiates the two repeated measurements is the independent variable of interest. Research on how to statistically test mediation, moderation, and conditional process models in these designs has been minimal. Judd, Kenny, and McClelland (2001) introduced a piece-wise method for testing for mediation, reminiscent of the Baron and Kenny causal steps approach for between-participant designs. Montoya and Hayes (2017) took thispiece-wise approach and translated it to a path-analytic approach, allowing for a quanti?cation of the indirect e?ect, more sophisticated methods of inference, and the extension to multiple mediator models. Moderation analysis in these designs has been described by Judd, McClelland, and Smith (1996), Judd et al. (2001), and Montoya (in press). However, the generalization to conditional process analysis, or moderated mediation, remains unknown. Describing this approach is the purpose of this dissertation.

scholarly journals Smartphone Addiction, Narcissism and Aggression: A Mediation Analysis Method

2019 ◽  
Author(s):  
Anjelica Simsek ◽  
Cahit Nuri ◽  
Cemaliye Direktor ◽  
Ahmet Arnavut
Keyword(s):  
Direct Effect ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Total Effect ◽  
Mediation Effect ◽  
Smartphone Addiction ◽  
Analysis Method ◽  
Variable Effect ◽  
Independent Variable ◽  
Mediator Variable

<p>At this study, meditation effect of aggression was analyzed using Baron and Kenny’s mediation analysis method. Baron and Kenny (1986) indicates that to analyze the effect of mediator variable 3 criteria have to be actualized:</p> <p>1. Independent variable have a significant effect on a mediator variable (way a)</p> <p>2. Mediator variable have a significant effect on a dependent variable (way b)</p> <p>3. Independent variable have a significant effect on a dependent variable (way c)</p> <p>PROCESS program were used the meditational effect, it is an extra macro that is downloading to the Daniel and Hayes’s (2016) SPSS program. In this program mediation effect could be evaluated as; total effect, direct effect and indirect effect scores of mediation variable effect on dependent variable (Preacher & Hayes, 2008).</p>

scholarly journals Using graphic modelling to identify modifiable mediators of the association between area-based deprivation at birth and offspring unemployment

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0249258
Author(s):  
James Bogie ◽  
Michael Fleming ◽  
Breda Cullen ◽  
Daniel Mackay ◽  
Jill P. Pell
Keyword(s):  
Public Health ◽  
Direct Effect ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
School Engagement ◽  
Directed Acyclic Graphs ◽  
Area Deprivation ◽  
Smoking During Pregnancy ◽  
Modifiable Factors ◽  
School Absences

Background Deprivation can perpetuate across generations; however, the causative pathways are not well understood. Directed acyclic graphs (DAG) with mediation analysis can help elucidate and quantify complex pathways in order to identify modifiable factors at which to target interventions. Methods and findings We linked ten Scotland-wide databases (six health and four education) to produce a cohort of 217,226 pupils who attended Scottish schools between 2009 and 2013. The DAG comprised 23 potential mediators of the association between area deprivation at birth and subsequent offspring ‘not in education, employment or training’ status, covering maternal, antenatal, perinatal and child health, school engagement, and educational factors. Analyses were performed using modified g-computation. Deprivation at birth was associated with a 7.3% increase in offspring ‘not in education, employment or training’. The principal mediators of this association were smoking during pregnancy (natural indirect effect of 0·016, 95% CI 0·013, 0·019) and school absences (natural indirect effect of 0·021, 95% CI 0·018, 0·024), explaining 22% and 30% of the total effect respectively. The proportion of the association potentially eliminated by addressing these factors was 19% (controlled direct effect when set to non-smoker 0·058; 95% CI 0·053, 0·063) for smoking during pregnancy and 38% (controlled direct effect when set to no absences 0·043; 95% CI 0·037, 0·049) for school absences. Conclusions Combining a DAG with mediation analysis helped disentangle a complex public health problem and quantified the modifiable factors of maternal smoking and school absence that could be targeted for intervention. This study also demonstrates the general utility of DAGs in understanding complex public health problems.

scholarly journals Conditional Process Analysis: Concepts, Computation, and Advances in the Modeling of the Contingencies of Mechanisms

2019 ◽  
Vol 64 (1) ◽  
pp. 19-54 ◽  
Author(s):  
Andrew F. Hayes ◽  
Nicholas J. Rockwood
Keyword(s):  
Boundary Conditions ◽  
Mediation Analysis ◽  
Process Model ◽  
Process Analysis ◽  
Ordinary Least Squares ◽  
Statistical Computing ◽  
Least Squares Regression ◽  
Analytical Strategy ◽  
Moderation Analysis ◽  
Conditional Process Analysis

Behavioral scientists use mediation analysis to understand the mechanism(s) by which an effect operates and moderation analysis to understand the contingencies or boundary conditions of effects. Yet how effects operate (i.e., the mechanism at work) and their boundary conditions (when they occur) are not necessarily independent, though they are often treated as such. Conditional process analysis is an analytical strategy that integrates mediation and moderation analysis with the goal of examining and testing hypotheses about how mechanisms vary as a function of context or individual differences. In this article, we provide a conceptual primer on conditional process analysis for those not familiar with the integration of moderation and mediation analysis, while also describing some recent advances and innovations for the more experienced conditional process analyst. After overviewing fundamental modeling principles using ordinary least squares regression, we discuss the extension of these fundamentals to models with more than one mediator and more than one moderator. We describe a differential dominance conditional process model and overview the concepts of partial, conditional, and moderated moderated mediation. We also discuss multilevel conditional process analysis and comment on implementation of conditional process analysis in statistical computing software.

scholarly journals Predictors of listening-related fatigue across the adult lifespan

2020 ◽  
Author(s):  
Ronan McGarrigle ◽  
Sarah Knight ◽  
Benjamin Hornsby ◽  
Sven Mattys
Keyword(s):  
Process Analysis ◽  
High Sensitivity ◽  
Auditory Attention ◽  
Adult Lifespan ◽  
Mediation Analyses ◽  
Age Related ◽  
Using Data ◽  
Conditional Process Analysis ◽  
The Impact ◽  
Age Related Changes

Listening-related fatigue is a potentially serious negative consequence of an aging auditory and cognitive system. However, the impact of age on listening-related fatigue, and the factors underpinning any such effect, remain unexplored. Using data from a large sample of adults (N = 281), we conducted a conditional process analysis to examine potential mediators and moderators of age-related changes in listening-related fatigue. Mediation analyses revealed opposing effects of age on listening-related fatigue; aging was associated with increased listening-related fatigue for individuals with higher self-reported hearing impairment, but also decreased listening-related fatigue via reductions in mood disturbance and sensory processing sensitivity (‘sensitivity’). Results also suggested that the effect of auditory attention ability on listening-related fatigue was moderated by sensitivity; for individuals with high sensitivity, better auditory attention ability was associated with increased fatigue. These findings shed light on the perceptual, cognitive, and psychological factors underlying age-related changes in listening-related fatigue.

Interculturalism and the Acceptance of Minority Groups

2020 ◽  
Vol 51 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Maykel Verkuyten ◽  
Kumar Yogeeswaran
Keyword(s):  
Minority Groups ◽  
Psychological Research ◽  
Survey Experiment ◽  
Social Psychological ◽  
Negative Attitudes ◽  
Positive Attitudes ◽  
Social Psychological Research ◽  
Using Data ◽  
The Impact ◽  
Situational Effect

Abstract. Multiculturalism has been criticized and rejected by an increasing number of politicians, and social psychological research has shown that it can lead to outgroup stereotyping, essentialist thinking, and negative attitudes. Interculturalism has been proposed as an alternative diversity ideology, but there is almost no systematic empirical evidence about the impact of interculturalism on the acceptance of migrants and minority groups. Using data from a survey experiment conducted in the Netherlands, we examined the situational effect of promoting interculturalism on acceptance. The results show that for liberals, but not for conservatives, interculturalism leads to more positive attitudes toward immigrant-origin groups and increased willingness to engage in contact, relative to multiculturalism.

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