scholarly journals Simulated gambling consumption mediation model (SGCMM): disentangling convergence with parallel mediation models

2020 ◽  
Vol 20 (3) ◽  
pp. 466-486
Author(s):  
Tim Brosowski ◽  
Tobias Turowski ◽  
Tobias Hayer
Keyword(s):  
Mediation Model ◽  
Simulated Gambling ◽  
Mediation Models ◽  
Gambling Consumption

scholarly journals MIMIC models for uniform and non-uniform DIF as moderated mediation models

2019 ◽  
Author(s):  
Amanda Kay Montoya ◽  
Minjeong Jeon
Keyword(s):  
Latent Variable ◽  
Moderated Mediation ◽  
Mediation Model ◽  
Mimic Models ◽  
Multiple Indicators ◽  
Moderated Mediation Model ◽  
Conditional Effects ◽  
Item Functioning ◽  
Uniform Differential Item Functioning ◽  
Mediation Models

In this note we describe how multiple indicators multiple cause (MIMIC) models for studying uniform and non-uniform differential item functioning (DIF) can be conceptualized as mediation and moderated mediation models. Conceptualizing DIF within the context of a moderated mediation model helps us understand DIF as the effect of some variable on our measurements which is not accounted for by the latent variable of interest. In addition, this allows us to apply useful concepts and ideas from the mediation and moderation literature: (1) improving our understanding of uniform and non-uniform DIF as direct effects and interactions, (2) understanding the implication of indirect effects in DIF analysis, (3) clarifying the interpretation of the “uniform DIF parameter” in the presence of non-uniform DIF, and (4) probing interactions and using the concept of “conditional effects” to better understand the patterns of DIF across the range of the latent variable.

scholarly journals Statistical Mediation Analysis for Models with a Binary Mediator and a Binary Outcome: the Differences Between Causal and Traditional Mediation Analysis

2021 ◽  
Author(s):  
Judith J. M. Rijnhart ◽  
Matthew J. Valente ◽  
Heather L. Smyth ◽  
David P. MacKinnon
Keyword(s):  
Mediation Analysis ◽  
Indirect Effects ◽  
Direct And Indirect Effects ◽  
Mediation Model ◽  
Binary Outcome ◽  
Binary Variables ◽  
Causal Mediation ◽  
Causal Mediation Analysis ◽  
Similarities And Differences ◽  
Mediation Models

AbstractMediation analysis is an important statistical method in prevention research, as it can be used to determine effective intervention components. Traditional mediation analysis defines direct and indirect effects in terms of linear regression coefficients. It is unclear how these traditional effects are estimated in settings with binary variables. An important recent methodological advancement in the mediation analysis literature is the development of the causal mediation analysis framework. Causal mediation analysis defines causal effects as the difference between two potential outcomes. These definitions can be applied to any mediation model to estimate natural direct and indirect effects, including models with binary variables and an exposure–mediator interaction. This paper aims to clarify the similarities and differences between the causal and traditional effect estimates for mediation models with a binary mediator and a binary outcome. Causal and traditional mediation analyses were applied to an empirical example to demonstrate these similarities and differences. Causal and traditional mediation analysis provided similar controlled direct effect estimates, but different estimates of the natural direct effects, natural indirect effects, and total effect. Traditional mediation analysis methods do not generalize well to mediation models with binary variables, while the natural effect definitions can be applied to any mediation model. Causal mediation analysis is therefore the preferred method for the analysis of mediation models with binary variables.

Perceived parental psychological control has indirect effects on aggression via need satisfaction and motivation for revenge

2018 ◽  
Vol 36 (9) ◽  
pp. 2857-2879 ◽  
Author(s):  
So Young Choe ◽  
Stephen J. Read
Keyword(s):  
Indirect Effects ◽  
Psychological Control ◽  
Need Satisfaction ◽  
Mediation Model ◽  
Parental Psychological Control ◽  
Path Models ◽  
Relationship Of ◽  
The Relationship ◽  
Shed Light ◽  
Mediation Models

We examined the relationship of perceived parental psychological control (PPC) to aggression and whether this relationship could be accounted for by indirect effects through need satisfaction and motivation for revenge. In our mediation models with need satisfaction, perceived PPC consistently shows indirect effects on aggression via the relatedness component of need satisfaction in all models, but not via the autonomy and competence components. Further, in a mediation model with vengeance only, psychologically controlled children reported greater motivation for revenge, which then predicted more aggression. In path models with the three needs and vengeance added in the later step, indirect effects through first thwarted need satisfaction and vengeance are significant, and the indirect effect via relatedness is most consistently significant. The results suggest that perceived PPC thwarts need satisfaction and motivates people to yearn for revenge, which facilitates aggression. Our findings can shed light on the mechanisms through which PPC facilitates aggression.

scholarly journals Role of Equanimity on the Mediation Model of Neuroticism, Perceived Stress and Depressive Symptoms

Healthcare ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1300
Author(s):  
Nahathai Wongpakaran ◽  
Tinakon Wongpakaran ◽  
Danny Wedding ◽  
Zsuzsanna Mirnics ◽  
Zsuzsanna Kövi
Keyword(s):  
Depressive Symptoms ◽  
Perceived Stress ◽  
Mental Health Problems ◽  
Moderated Mediation ◽  
Future Research ◽  
Mediation Model ◽  
Symptom Index ◽  
The Relationship ◽  
Mediation Models

Background: Equanimity is widely and commonly practiced, but few have investigated the concept in clinical research. While the mediation model of neuroticism, perceived stress and depression have been demonstrated, it remains unclear whether equanimity mediates the relationship of these variables in parallel, serial or moderated mediation models. This study aimed to investigate the role of equanimity among those models. Methods: In all, 644 general participants (74.2% female, mean age = 28.28 (SD = 10.6)) provided data on the 10-item Perceived Stress Scale (PSS), the Neuroticism Inventory (NI), depression subscale of the Core Symptom Index, and the equanimity subscale of the inner Strength-based Inventory. Mediation and moderation analyses with the 5000 bootstrapping method were applied. Results: Equanimity was shown to moderate the relationship between NI/PSS and depressive symptom. Statistical evaluation supported all parallel, serial and moderated mediation models. Equanimity as a moderator provided a higher amount of percent variance explained by depressive symptoms than parallel and serial mediation models. Conclusions: Results suggest that the effect of perceived stress and neuroticism on depression can be mitigated by increasing levels of equanimity. The results demonstrated one potential benefit from practicing equanimity; enabling its extension to mental health problems could constitute an interesting focus for future research.

scholarly journals Time and Other Considerations in Mediation Design

2017 ◽  
Vol 78 (6) ◽  
pp. 952-972 ◽  
Author(s):  
Meghan K. Cain ◽  
Zhiyong Zhang ◽  
C. S. Bergeman
Keyword(s):  
Type I Error ◽  
Error Rates ◽  
Mediation Effect ◽  
Type I ◽  
Mediation Model ◽  
Limited Data ◽  
Cross Sectional ◽  
Longitudinal Mediation ◽  
Indirect Path ◽  
Mediation Models

This article serves as a practical guide to mediation design and analysis by evaluating the ability of mediation models to detect a significant mediation effect using limited data. The cross-sectional mediation model, which has been shown to be biased when the mediation is happening over time, is compared with longitudinal mediation models: sequential, dynamic, and cross-lagged panel. These longitudinal mediation models take time into account but bring many problems of their own, such as choosing measurement intervals and number of measurement occasions. Furthermore, researchers with limited resources often cannot collect enough data to fit an appropriate longitudinal mediation model. These issues were addressed using simulations comparing four mediation models each using the same amount of data but with differing numbers of people and time points. The data were generated using multilevel mediation models, with varying data characteristics that may be incorrectly specified in the analysis models. Models were evaluated using power and Type I error rates in detecting a significant indirect path. Multilevel longitudinal mediation analysis performed well in every condition, even in the misspecified conditions. Of the analyses that used limited data, sequential mediation had the best performance; therefore, it offers a viable second choice when resources are limited. Finally, each of these models were demonstrated in an empirical analysis.

scholarly journals MIMIC Models for Uniform and Nonuniform DIF as Moderated Mediation Models

2019 ◽  
Vol 44 (2) ◽  
pp. 118-136
Author(s):  
Amanda K. Montoya ◽  
Minjeong Jeon
Keyword(s):  
Latent Variable ◽  
Moderated Mediation ◽  
Direct Effects ◽  
Mediation Model ◽  
Mimic Models ◽  
Multiple Indicators ◽  
Moderated Mediation Model ◽  
Conditional Effects ◽  
Item Functioning ◽  
Mediation Models

In this article, the authors describe how multiple indicators multiple cause (MIMIC) models for studying uniform and nonuniform differential item functioning (DIF) can be conceptualized as mediation and moderated mediation models. Conceptualizing DIF within the context of a moderated mediation model helps to understand DIF as the effect of some variable on measurements that is not accounted for by the latent variable of interest. In addition, useful concepts and ideas from the mediation and moderation literature can be applied to DIF analysis: (a) improving the understanding of uniform and nonuniform DIF as direct effects and interactions, (b) understanding the implication of indirect effects in DIF analysis, (c) clarifying the interpretation of the “uniform DIF parameter” in the presence of nonuniform DIF, and (d) probing interactions and using the concept of “conditional effects” to better understand the patterns of DIF across the range of the latent variable.

scholarly journals Mediation analysis methods used in observational research: a scoping review and recommendations

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Judith J. M. Rijnhart ◽  
Sophia J. Lamp ◽  
Matthew J. Valente ◽  
David P. MacKinnon ◽  
Jos W. R. Twisk ◽  
...  
Keyword(s):  
Mediation Analysis ◽  
Experimental Studies ◽  
Epidemiologic Studies ◽  
Sensitivity Analyses ◽  
Observational Research ◽  
Mediation Model ◽  
Causal Mediation ◽  
Analysis Methods ◽  
Causal Mediation Analysis ◽  
Mediation Models

Abstract Background Mediation analysis methodology underwent many advancements throughout the years, with the most recent and important advancement being the development of causal mediation analysis based on the counterfactual framework. However, a previous review showed that for experimental studies the uptake of causal mediation analysis remains low. The aim of this paper is to review the methodological characteristics of mediation analyses performed in observational epidemiologic studies published between 2015 and 2019 and to provide recommendations for the application of mediation analysis in future studies. Methods We searched the MEDLINE and EMBASE databases for observational epidemiologic studies published between 2015 and 2019 in which mediation analysis was applied as one of the primary analysis methods. Information was extracted on the characteristics of the mediation model and the applied mediation analysis method. Results We included 174 studies, most of which applied traditional mediation analysis methods (n = 123, 70.7%). Causal mediation analysis was not often used to analyze more complicated mediation models, such as multiple mediator models. Most studies adjusted their analyses for measured confounders, but did not perform sensitivity analyses for unmeasured confounders and did not assess the presence of an exposure-mediator interaction. Conclusions To ensure a causal interpretation of the effect estimates in the mediation model, we recommend that researchers use causal mediation analysis and assess the plausibility of the causal assumptions. The uptake of causal mediation analysis can be enhanced through tutorial papers that demonstrate the application of causal mediation analysis, and through the development of software packages that facilitate the causal mediation analysis of relatively complicated mediation models.

The Relation Between Aerobic Fitness and Cognitive Performance

2016 ◽  
Vol 30 (3) ◽  
pp. 102-113 ◽  
Author(s):  
Chun-Hao Wang ◽  
Chun-Ming Shih ◽  
Chia-Liang Tsai
Keyword(s):  
Cognitive Performance ◽  
Aerobic Fitness ◽  
Reaction Times ◽  
Mediation Model ◽  
Brain Potentials ◽  
Fitness Level ◽  
Eeg Data ◽  
Attention Performance ◽  
P3 Amplitude ◽  
The Relationship

Abstract. This study aimed to assess whether brain potentials have significant influences on the relationship between aerobic fitness and cognition. Behavioral and electroencephalographic (EEG) data was collected from 48 young adults when performing a Posner task. Higher aerobic fitness is related to faster reaction times (RTs) along with greater P3 amplitude and shorter P3 latency in the valid trials, after controlling for age and body mass index. Moreover, RTs were selectively related to P3 amplitude rather than P3 latency. Specifically, the bootstrap-based mediation model indicates that P3 amplitude mediates the relationship between fitness level and attention performance. Possible explanations regarding the relationships among aerobic fitness, cognitive performance, and brain potentials are discussed.

Sign in / Sign up

Export Citation Format

Share Document