| Title: | A comparative study of multiple parallel mediation analysis methods |
| Journal: | Chinese Journal of Epidemiology |
| Published: | 10 May 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35589582/ |
| DOI: | https://doi.org/10.3760/cma.j.cn112338-20211022-00814 |
Publication 12378
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Abstract
Objective To introduce and compare four analysis methods of multiple parallel mediation model, including pure regression method, method based on inverse probability weighting, extended natural effect model method and weight-based imputation strategies. Methods For the multiple parallel mediation model, the simulation experiments of three scenarios were carried out to compare the performance of different methods in estimating direct and indirect effects in different situations. Dataset from UK Biobank was then analyzed by using the four methods. Results The estimation biases of the regression method and the inverse probability weighting method were relatively small, followed by the extended natural effect model method, and the estimation results of the weight-based imputation strategies were quite different from the other three methods. Conclusions Different multiple parallel mediation analysis methods have different application situations and their own advantages and disadvantages. The regression method is more suitable for continuous mediator, and the inverse probability weighting method is more suitable for binary mediator. The extended natural effect model method has better performances when the residuals of two parallel mediators are positively correlated and the correlation degree is small. The weight-based imputation strategies might not be appropriate for parallel mediation analysis. Therefore, appropriate methods should be selected according to the specific situation in practice.</p>
8 Keywords
- Bias
- Computer Simulation
- Humans
- Mediation Analysis
- Models, Statistical
- Probability
- Regression Analysis
- Research Design
4 Authors
- 于洋
- 仇沁晓
- 尤东方
- 赵杨
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