scholarly journals Longitudinal Mediation Analysis Using Natural Effect Models

2020 ◽  
Vol 189 (11) ◽  
pp. 1427-1435 ◽  
Author(s):  
Murthy N Mittinty ◽  
Stijn Vansteelandt
Keyword(s):  
Indirect Effect ◽  
Mediation Analysis ◽  
Total Effect ◽  
Inverse Probability ◽  
Effect Decomposition ◽  
The United Kingdom ◽  
Longitudinal Measurements ◽  
Measured Time ◽  
Structural Mean Models ◽  
Time Point

Abstract Mediation analysis is concerned with the decomposition of the total effect of an exposure on an outcome into the indirect effect, through a given mediator, and the remaining direct effect. This is ideally done using longitudinal measurements of the mediator, which capture the mediator process more finely. However, longitudinal measurements pose challenges for mediation analysis, because the mediators and outcomes measured at a given time point can act as confounders for the association between mediators and outcomes at a later time point; these confounders are themselves affected by the prior exposure and outcome. Such posttreatment confounding cannot be dealt with using standard methods (e.g., generalized estimating equations). Analysis is further complicated by the need for so-called cross-world counterfactuals to decompose the total effect. This work addresses these challenges. In particular, we introduce so-called natural effect models, which parameterize the direct and indirect effect of a baseline exposure with respect to a longitudinal mediator and outcome. These can be viewed as a generalization of marginal structural mean models to enable effect decomposition. We introduce inverse probability weighting techniques for fitting these models, adjusting for (measured) time-varying confounding of the mediator-outcome association. Application of this methodology uses data from the Millennium Cohort Study, a longitudinal study of children born in the United Kingdom between September 2000 and January 2002.

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 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 Do Age at Diagnosis, Tumour Thickness and Tumour Site Explain Sex Differences in Melanoma Survival? A Sequential Causal Mediation Analysis Using Cancer Registry Data

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 33s-33s
Author(s):  
N. Afshar ◽  
S.G. Dashti ◽  
V. Thursfield ◽  
H. Farrugia ◽  
G.G. Giles ◽  
...  
Keyword(s):  
Sex Differences ◽  
Cancer Registry ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Tumor Thickness ◽  
Total Effect ◽  
Age At Diagnosis ◽  
Tumor Site ◽  
Cancer Registry Data ◽  
Causal Mediation Analysis

Background: Previous research has shown that women diagnosed with melanoma have better survival than their male counterparts, but little is known about the underlying mechanisms by which sex affects melanoma survival. Aim: The aim of this study was to quantify the contribution of age at diagnosis, tumor thickness and tumor site to sex differences in 1-year and 5-year melanoma-specific survival. Methods: We conducted a population-based study using cancer registry data including 6,009 men and 5,232 women aged 15-70 years with first primary melanoma diagnosed between 2007 and 2015 in Victoria, Australia. We excluded cases notified via death certificate only. Deaths to the end of 2015 were identified through linkage to the Victorian and national death registries. We decomposed the total effect of sex on melanoma-specific survival into three possible pathways, examining the mediating role of age at diagnosis, tumor thickness and tumor site. The natural indirect effects through the mediators were assessed using weighted, sequential causal mediation analysis. Results: Compared with women, there were 60 (95% confidence interval (CI) 34 to 91) and 201 (95% CI 135 to 267) additional deaths per 10,000 in men within 1 year and 5 years following diagnosis, respectively. Within 1 year following diagnosis, the indirect effect through age at diagnosis was estimated to be 4 (95% CI -2 to 9) additional deaths per 10,000 in men compared with women, explaining 7% of the total effect of sex, while a considerable proportion of the total effect (79%) explained by melanoma thickness [47 (95% CI 32 to 66) additional deaths per 10,000 in men], excluding the potential influence of age at diagnosis on thickness. Similarly, within 5 years after diagnosis, about 13% of the total effect was estimated to be explained by age at diagnosis [26 (95% CI 15 to 38) additional deaths per 10,000 in men] and 86% by tumor thickness [174 (95% CI 142 to 207) additional death per 10,000 in men]. There was no indirect effect through tumor site within 1 year and 5 years postdiagnosis. Conclusion: The lower survival from melanoma of men relative to women appears to be explained primarily by tumor thickness rather than age at diagnosis. Our findings highlight the need for earlier detection of melanoma in men.

Two-Condition Within-Participant Statistical Mediation Analysis: A Path-Analytic Framework

2019 ◽  
Author(s):  
Amanda Kay Montoya ◽  
Andrew F. Hayes
Keyword(s):  
Confidence Intervals ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Analytic Approach ◽  
Analytic Framework ◽  
Hypothesis Tests ◽  
Bootstrap Confidence Intervals ◽  
Complex Models ◽  
Path Analytic ◽  
Statistical Mediation Analysis

Researchers interested in testing mediation often use designs where participants are measured on a dependent variable Y and a mediator M in both of two different circumstances. The dominant approach to assessing mediation in such a design, proposed by Judd, Kenny, and McClelland (2001), relies on a series of hypothesis tests about components of the mediation model and is not based on an estimate of or formal inference about the indirect effect. In this paper we recast Judd et al.’s approach in the path-analytic framework that is now commonly used in between-participant mediation analysis. By so doing, it is apparent how to estimate the indirect effect of a within-participant manipulation on some outcome through a mediator as the product of paths of influence. This path analytic approach eliminates the need for discrete hypothesis tests about components of the model to support a claim of mediation, as Judd et al’s method requires, because it relies only on an inference about the product of paths— the indirect effect. We generalize methods of inference for the indirect effect widely used in between-participant designs to this within-participant version of mediation analysis, including bootstrap confidence intervals and Monte Carlo confidence intervals. Using this path analytic approach, we extend the method to models with multiple mediators operating in parallel and serially and discuss the comparison of indirect effects in these more complex models. We offer macros and code for SPSS, SAS, and Mplus that conduct these analyses.

scholarly journals Acculturation, Communication Competence, and Family Functioning in Mexican–American Mother–Daughter Dyads

2021 ◽  
Author(s):  
Becky Marquez ◽  
Tanya Benitez ◽  
Zephon Lister
Keyword(s):  
Family Functioning ◽  
Relationship Quality ◽  
Communication Skills ◽  
Adult Children ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Mexican American ◽  
Communication Competence ◽  
Well Being ◽  
Actor Partner Interdependence Model

AbstractLittle is known of how intergenerational acculturation discrepancy relates to communication skills differences that may influence relationship quality among parents and adult children. Mexican–American mother–daughter dyads (n = 59) were studied using the Actor Partner Interdependence Model to examine dyadic associations of acculturation and communication competence with family functioning and mediation analysis to determine the indirect effect of acculturation discrepancy on family functioning through communication competence differences. Communication competence of mothers exerted significant actor and partner effects on daughter-perceived cohesion and closeness. Higher acculturation discrepancy predicted greater communication competence difference which in turn was associated with lower cohesion and closeness. There was a significant indirect effect of acculturation discrepancy on daughter-perceived cohesion through communication competence difference. Communication competence of mothers impacts their own as well as their daughters’ perceptions of dyad cohesion and closeness. Intergenerational discrepant acculturation contributes to discordant communication skills that impair family functioning, which has implications for psychological well-being.

scholarly journals Exact parametric causal mediation analysis for a binary outcome with a binary mediator

2021 ◽  
Author(s):  
Marco Doretti ◽  
Martina Raggi ◽  
Elena Stanghellini
Keyword(s):  
Logistic Regression ◽  
Direct Effect ◽  
Mediation Analysis ◽  
Delta Method ◽  
Binary Outcome ◽  
Effect Decomposition ◽  
Causal Mediation ◽  
Regression Parameters ◽  
Causal Mediation Analysis ◽  
Parametric Expression

AbstractWith reference to causal mediation analysis, a parametric expression for natural direct and indirect effects is derived for the setting of a binary outcome with a binary mediator, both modelled via a logistic regression. The proposed effect decomposition operates on the odds ratio scale and does not require the outcome to be rare. It generalizes the existing ones, allowing for interactions between both the exposure and the mediator and the confounding covariates. The derived parametric formulae are flexible, in that they readily adapt to the two different natural effect decompositions defined in the mediation literature. In parallel with results derived under the rare outcome assumption, they also outline the relationship between the causal effects and the correspondent pathway-specific logistic regression parameters, isolating the controlled direct effect in the natural direct effect expressions. Formulae for standard errors, obtained via the delta method, are also given. An empirical application to data coming from a microfinance experiment performed in Bosnia and Herzegovina is illustrated.

Abstract P238: Importance of Self-Efficacy in the Patient-Reported Physical Function of Patients With Stroke

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Irene L Katzan ◽  
Dolora R Wisco ◽  
Brittany Lapin
Keyword(s):  
Physical Function ◽  
Indirect Effect ◽  
Self Efficacy ◽  
Total Effect ◽  
Pain Interference ◽  
Study Cohort ◽  
Stressful Situation ◽  
Study Objective ◽  
Patient Reported ◽  
The Relationship

Background: Self-efficacy is the belief that one is able to respond to demands of a stressful situation and it has both direct and indirect effects on health. The study objective is to investigate the amount of variance in patient-reported physical function (PF) that is explained by self-efficacy compared to clinician-reported disability and other patient-reported domains of health, and evaluate whether self-efficacy mediates the relationship between PF and other domains of health. Methods: Observational cohort study of 248 patients who were seen in a cerebrovascular clinic 3/18/20 - 7/7/20 and completed the following patient-reported outcome measures (PROMs) as part of the routine office visit: PROMIS PF, general self-efficacy, fatigue, and pain interference. Linear regression models were constructed to determine the amount of variance (adjusted R 2 ) in PROMIS PF score explained by the modified Rankin Scale (mRS) and additional PROM scores. The mRS and individual PROMs were added separately to a base model adjusted for demographic characteristics. Mediation analysis was conducted to determine the extent to which self-efficacy mediated the relationship between PF and other PROMs. Results: Mean age of study cohort was 61.5 (SD=13.5) years and 48.4% were female. The base model explained 4.5% of the variance of PF. Adding PROMIS fatigue resulted in the largest increase in the proportion of variance explained (adj R 2 = 47.7%), followed by PROMIS self-efficacy (40.7%), PROMIS pain interference (38.7%), and mRS (26.6%). Self-efficacy significantly mediated the relationship between fatigue and PF (standardized indirect effect: 0.11 (bias-corrected 95% CI: 0.05-0.18), 20.9% of total effect) and pain interference and PF (standardized indirect effect 0.10 (95% CI: 0.06-0.17), 27.1% of total effect). Conclusion: PROMIS self-efficacy explains more variance in stroke patients’ perceived physical function than their disability. This suggests that interventions to improve self-efficacy could have a significant effect on patient’s perceived health. Patients’ fatigue, despite being partially mediated by self-efficacy, was a large contributor to self-reported PF and should be included as part of an evaluation of patient’s physical health.

scholarly journals How do I know what my theory predicts

2019 ◽  
Author(s):  
Zoltan Dienes
Keyword(s):  
Mediation Analysis ◽  
Null Hypothesis ◽  
Prior Information ◽  
Bayes Factor ◽  
Total Effect ◽  
Ways Of Thinking ◽  
Regression Slopes ◽  
Mean Differences ◽  
Simple Heuristics

To get evidence for or against a theory relative to the null hypothesis, one needs to know what the theory predicts. The amount of evidence can then be quantified by a Bayes factor. Specifying what one's theory predicts may not come naturally, but I show some ways of thinking about the problem, some simple heuristics that are often useful when one has little relevant prior information. These heuristics include the room-to-move heuristic (for comparing mean differences), the ratio-of-scales heuristic (for regression slopes), the ratio-of-means heuristic (for regression slopes), the basic effect heuristic (for ANOVA effects), and the total effect heuristic (for mediation analysis).

Mediating Effect of C-reactive Protein and Aspartate Aminotransferase on Diabetes Mellitus and Myocardial Infarction Risk

2020 ◽  
Author(s):  
Hui Zhao ◽  
Miao-miao Jiang ◽  
Sang Hu ◽  
Chang Su ◽  
Li Zhang ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Mediation Analysis ◽  
Mediating Effect ◽  
Total Effect ◽  
Mediation Effect ◽  
Risk Level ◽  
Mediation Model ◽  
Reactive Protein ◽  
Unit Increase ◽  
The Relationship

Abstract Background: The relationship between diabetes and myocardial infarction has always been the focus of research, but it is not clear whether the DM-MI association is direct or mediated by other factors. Our hypothesis is that part of the risk of MI in DM patients may be mediated by CRP and AST. We examined this hypothesis in the mediation analysis and tried to assess the extent to which CRP and AST could explain the MI risk caused by DM.Methods: This case-control study was conducted on 130 patients with MI and 130 patients with no-MI. We compared the relevant biochemical indicators of MI and no-MI patients, and applied mediation analysis to test the association of CRP and AST with DM-MI Potential adjustment effect.Results: The study found that individuals who suffered MI were more likely to have DM as compared with Non-MI (OR = 2.117, 95%CI = 1.130-4.195, P = 0.020), and CRP and AST are positively correlated with the occurrence of MI, For every unit increase in CRP and AST levels, the risk level of MI Significantly increased by 1%, 3.1% respectively. The direct effect of DM and MI is 0.847, the mediating effect of CRP is 7.69% of the total effect, and the mediating effect of AST is 52.79% of the total effect. The mediation effect of the CRP-AST path is 0.386, accounting for 12.36% of the total effect. In the mediation model we verified, CRP and AST play a part of the mediation effect between DM with MI, and the total mediation effect accounts for 72.84%.Conclusions: CRP and AST play an important role in the risk of DM-induced MI. This provides evidence for the mechanism and is of great significance for the exploration of therapeutic targets.

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