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. 2024 Nov;86(2):669-689.
doi: 10.1007/s13571-024-00336-w. Epub 2024 Jul 2.

Mediation Analysis using Semi-parametric Shape-Restricted Regression with Applications

Qing Yin  1 , Jong-Hyeon Jeong  2 , Xu Qin  3 , Shyamal D Peddada  4 , Jennifer J Adibi  5
Affiliations

Mediation Analysis using Semi-parametric Shape-Restricted Regression with Applications

Qing Yin et al. Sankhya Ser B. 2024 Nov.

Abstract

Often linear regression is used to estimate mediation effects. In many instances the underlying relationships may not be linear. Although, the exact functional form of the relationship may be unknown, based on the underlying science, one may hypothesize the shape of the relationship. For these reasons, we develop a novel shape-restricted inference-based methodology for conducting mediation analysis. This work is motivated by an application in fetal endocrinology where researchers are interested in understanding the effects of pesticide application on birth weight, with human chorionic gonadotropin (hCG) as the mediator. Using the proposed methodology on a population-level prenatal screening program data, with hCG as the mediator, we discovered that while the natural direct effects suggest a positive association between pesticide application and birth weight, the natural indirect effects were negative.

Keywords: Birth-weight; Constrained inference; Human chorionic gonadotropin (hCG); Mediation analysis; Pesticides exposure; Placental-fetal hormones; Regression spline; Shape-restricted inference.

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Conflict of interest statement

Conflict of Interest Authors declare no conflict of interests.

Figures

Fig. 1
Fig. 1
The relationship between a placental hormone (expressed as a gestational age multiple of median) and infant birth weight
Fig. 2
Fig. 2
Plots of hormone vs. birth weight under each pattern, and simulation results of coverage probability for each pattern
Fig. 3
Fig. 3
The directed acyclic graph (DAG) for the analysis
See this image and copyright information in PMC

Update of

References

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