Assessing Omitted Confounder Bias in Multilevel Mediation Models
1a School of Psychology , Georgia Institute of Technology.
Multivariate Behavioral Research
|February 17, 2016
Summary
Ensuring no omitted confounders is crucial for accurate mediation analysis. This study examines how unaddressed confounders bias multilevel mediation and offers a sensitivity analysis to check results.
Area of Science:
- Multilevel mediation analysis
- Causal inference
- Statistical modeling
Background:
- Valid inference in mediation models requires the absence of omitted confounders, which are common causes of hypothesized relationships.
- Violating the no-omitted-confounder assumption can lead to biased indirect effect estimates and misleading conclusions in mediation analysis.
- While confounder bias is studied in single-level mediation, it remains under-addressed in multilevel mediation.
Purpose of the Study:
- To analytically examine the biasing effects of omitted Level 1 confounders in two-level mediation models with random intercepts and slopes.
- To propose a sensitivity analysis technique for assessing the impact of potential no-omitted-confounder assumption violations on indirect effect conclusions.
- To provide practical tools and illustrations for researchers conducting multilevel mediation analysis.
Main Methods:
- Analytical examination of bias due to omitted Level 1 confounders in a two-level mediation model.
- Development and application of a sensitivity analysis technique to evaluate assumption violations.
- Illustration with an empirical study and provision of accompanying computer code.
Main Results:
- Omitting a Level 1 confounder can significantly bias estimates of both Level 1 and Level 2 indirect effects in multilevel mediation.
- The proposed sensitivity analysis quantifies the potential impact of omitted confounders on observed indirect effects.
- The methods are demonstrated to be applicable in real-world research scenarios.
Conclusions:
- The no-omitted-confounder assumption is critical and untestable in multilevel mediation, necessitating sensitivity analyses.
- Researchers should be aware of potential confounding at Level 1 and its impact on indirect effects.
- The proposed sensitivity analysis technique offers a valuable tool for enhancing the robustness of multilevel mediation findings.
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