Hypothesis test of mediation effect in causal mediation model with high-dimensional continuous mediators

Biometrics ◽  
2015 ◽  
Vol 72 (2) ◽  
pp. 402-413 ◽  
Author(s):  
Yen-Tsung Huang ◽  
Wen-Chi Pan
Keyword(s):  
Hypothesis Test ◽  
Mediation Effect ◽  
High Dimensional ◽  
Mediation Model ◽  
Causal Mediation

scholarly journals Estimating and testing the microbial causal mediation effect with high-dimensional and compositional microbiome data

2019 ◽  
Author(s):  
Chan Wang ◽  
Jiyuan Hu ◽  
Martin J Blaser ◽  
Huilin Li
Keyword(s):  
Regression Model ◽  
Association Studies ◽  
Statistical Significance ◽  
Mediation Effect ◽  
Supplementary Information ◽  
High Dimensional ◽  
Model Framework ◽  
Mediation Effects ◽  
Causal Mediation ◽  
Microbiome Data

Abstract Motivation Recent microbiome association studies have revealed important associations between microbiome and disease/health status. Such findings encourage scientists to dive deeper to uncover the causal role of microbiome in the underlying biological mechanism, and have led to applying statistical models to quantify causal microbiome effects and to identify the specific microbial agents. However, there are no existing causal mediation methods specifically designed to handle high dimensional and compositional microbiome data. Results We propose a rigorous Sparse Microbial Causal Mediation Model (SparseMCMM) specifically designed for the high dimensional and compositional microbiome data in a typical three-factor (treatment, microbiome and outcome) causal study design. In particular, linear log-contrast regression model and Dirichlet regression model are proposed to estimate the causal direct effect of treatment and the causal mediation effects of microbiome at both the community and individual taxon levels. Regularization techniques are used to perform the variable selection in the proposed model framework to identify signature causal microbes. Two hypothesis tests on the overall mediation effect are proposed and their statistical significance is estimated by permutation procedures. Extensive simulated scenarios show that SparseMCMM has excellent performance in estimation and hypothesis testing. Finally, we showcase the utility of the proposed SparseMCMM method in a study which the murine microbiome has been manipulated by providing a clear and sensible causal path among antibiotic treatment, microbiome composition and mouse weight. Availability and implementation https://sites.google.com/site/huilinli09/software and https://github.com/chanw0/SparseMCMM. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Estimating and testing the microbial causal mediation effect with high-dimensional and compositional microbiome data

2019 ◽  
Author(s):  
Chan Wang ◽  
Jiyuan Hu ◽  
Martin J. Blaser ◽  
Huilin Li
Keyword(s):  
Regression Model ◽  
Association Studies ◽  
Statistical Significance ◽  
Mediation Effect ◽  
High Dimensional ◽  
Model Framework ◽  
Mediation Effects ◽  
Microbiome Composition ◽  
Causal Mediation ◽  
Microbiome Data

AbstractMotivationRecent microbiome association studies have revealed important associations between microbiome and disease/health status. Such findings encourage scientists to dive deeper to uncover the causal role of microbiome in the underlying biological mechanism, and have led to applying statistical models to quantify causal microbiome effects and to identify the specific microbial agents. However, there are no existing causal mediation methods specifically designed to handle high dimensional and compositional microbiome data.ResultsWe propose a rigorous Sparse Microbial Causal Mediation Model (SparseMCMM) specifically designed for the high dimensional and compositional microbiome data in a typical three-factor (treatment, microbiome and outcome) causal study design. In particular, linear log-contrast regression model and Dirichlet regression model are proposed to estimate the causal direct effect of treatment and the causal mediation effects of microbiome at both the community and individual taxon levels. Regularization techniques are used to perform the variable selection in the proposed model framework to identify signature causal microbes. Two hypothesis tests on the overall mediation effect are proposed and their statistical significance is estimated by permutation procedures. Extensive simulated scenarios show that SparseMCMM has excellent performance in estimation and hypothesis testing. Finally, we showcase the utility of the proposed SparseMCMM method in a study which the murine microbiome has been manipulated by providing a clear and sensible causal path among antibiotic treatment, microbiome composition and mouse weight.

scholarly journals Influence of Self-Esteem of Middle School Students for Mental Care on Academic Achievement: Based on the Mediation Effect of GRIT and Academic Enthusiasm

2021 ◽  
Vol 18 (13) ◽  
pp. 7025
Author(s):  
Jhong Yun (Joy) Kim ◽  
EunBee Kim ◽  
InSu Lee
Keyword(s):  
Middle School ◽  
Academic Achievement ◽  
Middle School Students ◽  
First Graders ◽  
Self Esteem ◽  
Study Data ◽  
Mediation Effect ◽  
Mediation Model ◽  
School Students ◽  
Mental Care

The purpose of this study is to identify how self-esteem of middle school students for mental care influences their academic achievement and to verify the mediation effect of GRIT on academic enthusiasm. Data of 2590 first graders in middle school from the Kora Children and Youth Panel Survey 2019 was used to support this study. Data analysis was performed by using SPSS21.0, AMOS22.0, and PROCESS macro program. The results are as follows. Comparison of the model fits of each full mediation model and partial mediation model with χ2 showed that the full mediation model was more suitable for this study. In more detail, the influence of self-esteem on GRIT and the influence of GRIT on academic enthusiasm were significantly positive. Lastly, the study identified that there was a mediation effect between self-esteem and academic achievement through GRIT and academic enthusiasm. It indicates that self-esteem is the key to improve academic achievement and that specific programs should be supplemented in order to enhance self-esteem, GRIT, and academic enthusiasm.

scholarly journals The mediation effect of serum metabolites on the relationship between long-term smoking exposure and esophageal squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mengke Wei ◽  
Lihong Zhao ◽  
Jiali Lv ◽  
Xia Li ◽  
Guangshuai Zhou ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cigarette Smoking ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cholic Acid ◽  
Mediation Analysis ◽  
Mediation Effect ◽  
High Dimensional ◽  
Smoking Exposure ◽  
Smoking Index

Abstract Background Long-term smoking exposure will increase the risk of esophageal squamous cell carcinoma (ESCC), whereas the mechanism is still unclear. We conducted a cross-sectional study to explore whether serum metabolites mediate the occurrence of ESCC caused by cigarette smoking. Methods Serum metabolic profiles and lifestyle information of 464 participants were analyzed. Multiple logistic regression was used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of smoking exposure to ESCC risk. High-dimensional mediation analysis and univariate mediation analysis were performed to screen potential intermediate metabolites of smoking exposure for ESCC. Results Ever smoking was associated with a 3.11-fold increase of ESCC risk (OR = 3.11, 95% CI 1.63–6.05), and for each cigarette-years increase in smoking index, ESCC risk increased by 56% (OR = 1.56, 95% CI 1.18–2.13). A total of 5 metabolites were screened as mediators by high-dimensional mediation analysis. In addition, glutamine, histidine, and cholic acid were further proved existing mediation effects according to univariate mediation analysis. And the proportions of mediation of histidine and glutamine were 40.47 and 30.00%, respectively. The mediation effect of cholic acid was 8.98% according to the analysis of smoking index. Conclusions Our findings suggest that cigarette smoking contributed to incident ESCC, which may be mediated by glutamine, histidine and cholic acid.

scholarly journals Variable selection for causal mediation analysis using LASSO-based methods

2021 ◽  
pp. 096228022199750
Author(s):  
Zhaoxin Ye ◽  
Yeying Zhu ◽  
Donna L Coffman
Keyword(s):  
Propensity Score ◽  
Indirect Effect ◽  
Adaptive Lasso ◽  
Mediation Effect ◽  
Regularization Methods ◽  
Causal Mediation ◽  
Outcome Information ◽  
Causal Mediation Analysis ◽  
Selection For ◽  
Mimic Iii

Causal mediation effect estimates can be obtained from marginal structural models using inverse probability weighting with appropriate weights. In order to compute weights, treatment and mediator propensity score models need to be fitted first. If the covariates are high-dimensional, parsimonious propensity score models can be developed by regularization methods including LASSO and its variants. Furthermore, in a mediation setup, more efficient direct or indirect effect estimators can be obtained by using outcome-adaptive LASSO to select variables for propensity score models by incorporating the outcome information. A simulation study is conducted to assess how different regularization methods can affect the performance of estimated natural direct and indirect effect odds ratios. Our simulation results show that regularizing propensity score models by outcome-adaptive LASSO can improve the efficiency of the natural effect estimators and by optimizing balance in the covariates, bias can be reduced in most cases. The regularization methods are then applied to MIMIC-III database, an ICU database developed by MIT.

Effects of perceived social isolation, fear of social isolation and gratitude during COVID-19 pandemic on anxiety in Malaysia (Preprint)

2021 ◽  
Author(s):  
Cher Yi Tan ◽  
Jia Yi Ng ◽  
Mei-Hua Lin ◽  
Min Hooi Yong
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Social Isolation ◽  
Indirect Effect ◽  
Moderating Effect ◽  
Mediating Effect ◽  
Mediation Effect ◽  
Mediation Model ◽  
Middle Aged ◽  
Perceived Social Isolation

BACKGROUND The COVID-19 pandemic compelled many countries including Malaysia to impose movement restrictions to curb spreading the virus. Evidence shows that prolonged isolation has negative effects on both physical and mental health. OBJECTIVE Our aims were to examine (1) the mediating effect of perceived social isolation (SI) and fear of social isolation (FSI) on the relationship between gratitude and anxiety, and (2) to explore the moderating effect of age, education and socioeconomic status on the mediation model. METHODS We collected data from 427 participants currently living in Malaysia during the movement restriction order (Mage = 37.90, SD = 16.51, 313 females) from an online survey containing questions pertaining to isolation and gratitude. RESULTS Our mediation analysis showed that gratitude has a positive effect on overcoming anxiety as it also lowers feelings of SI and FSI (B = -.229, β = .128, bootstrap SE = .049, 95% bootstrap CI = [-.332, -.138]). The moderated mediation analyses revealed the indirect effect of gratitude on anxiety through SI was significant for young adults (B = -.148, β = .083, 95% bootstrap CI [-.274, -.042]) and middle-aged (B = -.099, β = -.055, 95% bootstrap CI [-.177, -.033]) but not for older adults (B = -.026, β = -.015, 95% bootstrap CI [-.129, .047]). Results were similar for FSI in that it was significant for middle aged and not significant for older adults (all CIs does not include zero). However the mediation effect was not significant for young adults (B = -.020, β = -.011, 95% bootstrap CI [-.066, .016]). When we examined the moderating effect of education and SES in the parallel mediation model, results showed that the mediation effect of SI and FSI for those with lower levels of education was significant for all SES levels (all CIs did not contain zero). As for those with medium levels of education, the conditional indirect effect of SI and FSI was significant only for low and medium levels of SES but not for high SES. CONCLUSIONS Our findings highlight the importance of having some coping mechanism and social connection during the pandemic to have higher wellbeing and quality of life, especially for middle-aged sample and people from low education and SES background. CLINICALTRIAL None

scholarly journals Causal mediation analysis with multiple causally non-ordered mediators

2015 ◽  
Vol 27 (1) ◽  
pp. 3-19 ◽  
Author(s):  
Masataka Taguri ◽  
John Featherstone ◽  
Jing Cheng
Keyword(s):  
Indirect Effect ◽  
Interactive Effect ◽  
Mediation Effect ◽  
Mediation Effects ◽  
Mediation Analyses ◽  
Intermediate Variable ◽  
Causal Mediation ◽  
Health Studies ◽  
Using Data ◽  
The Individual

In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation analyses with one mediator at a time. In this article, we consider mediation analyses when there are causally non-ordered multiple mediators. Even if the mediators do not affect each other, the sum of two indirect effects through the two mediators considered separately may diverge from the joint natural indirect effect when there are additive interactions between the effects of the two mediators on the outcome. Therefore, we derive an equation for the joint natural indirect effect based on the individual mediation effects and their interactive effect, which helps us understand how the mediation effect works through the two mediators and relative contributions of the mediators and their interaction. We also discuss an extension for three mediators. The proposed method is illustrated using data from a randomized trial on the prevention of dental caries.

scholarly journals Working Alliance as a Mediator between Supervisory Styles and Supervisee Satisfaction

2021 ◽  
Author(s):  
Dan Li ◽  
David K. Duys ◽  
Yanhong Liu
Keyword(s):  
Working Alliance ◽  
Counselor Trainees ◽  
Research Question ◽  
Mediation Effect ◽  
Supervisory Working Alliance ◽  
Mediation Model ◽  
Professional Networks ◽  
Supervisory Styles ◽  
Satisfaction With Supervision ◽  
Balanced Approach

To answer the research question whether there is a mediation effect of the supervisory working alliance between supervisory styles and supervisee satisfaction, we developed a mediation model and tested this hypothesized mediation effect with a sample of 111 participants that was comprised of master’s and doctoral counselor trainees and counseling practitioners recruited from several counseling professional networks. Results indicated a statistically significant indirect effect of supervisory styles on supervisee satisfaction through the supervisory working alliance. Specifically, when supervisees rated higher on a mixture of three supervisory styles, they were more likely to report a stronger working alliance with their supervisors; this alliance, in turn, contributed to their higher levels of satisfaction with supervision. These findings also speak to the importance of maintaining a flexible, balanced approach in supervision, and shed light on how both supervisors and supervisees can contribute to the supervisory working alliance so as to enhance supervisee satisfaction.

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.

scholarly journals Influences on the Implementation of Community Urban Agriculture: Insights from Agricultural Professionals

2019 ◽  
Vol 11 (5) ◽  
pp. 1422 ◽  
Author(s):  
Neda Tiraieyari ◽  
Roya Karami ◽  
Robert Ricard ◽  
Mohammad Badsar
Keyword(s):  
Direct Effect ◽  
Urban Agriculture ◽  
Personal Characteristics ◽  
Mediation Effect ◽  
Negative Consequences ◽  
Mediation Model ◽  
Internal Factors ◽  
Policy Makers ◽  
Policy Interventions ◽  
Agricultural Professionals

Limited studies have investigated the relative influence of both external and internal factors in the implementation of community-based urban agriculture (UA) (ICUA). Furthermore, little research exists explaining how different mechanisms might influence urban residents’ decision to participate in UA. Our research tested the direct effect of several predictors on ICUA using structural equational modelling. In addition, we tested the mediation effect between the predictors and the ICUA that may exist as well. Results are based on data from 200 agricultural professionals in the Zanjan province in northwest Iran. We found that “personal characteristics”, “UA positive and negative consequences”, “sociocultural”, and “economic” factors affect ICUA. Among all factors, “personal characteristics” had the strongest direct effect on ICUA. The indirect model incorporating “attitude” provided support for the mediation model. We found “personal characteristics”, “UA positive and negative consequences”, and “sociocultural” influenced ICUA indirectly through “attitude.” Among all factors, “sociocultural” had the strongest indirect effect on ICUA. This information is of use to policy-makers and program planners in identifying points of policy interventions and mechanisms for promoting UA.

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