SRMERS: Semi-Parametric Shape-Restricted Fixed/Mixed Effect(s) Regression Spline

2026 Dataset Open access

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Authors: Qing Yin, Shyamal D. Peddada, Jennifer Joan Adibi, Jong-Hyeon Jeong
DOI: 10.32614/cran.package.srmers
Cited by: 0
References: 2

Abstract

Select the most suitable shape to describe the relationship between the exposure and the outcome among increasing, decreasing, convex, and concave shapes (Yin et al. (2021) ); estimate the direct and indirect effects with prior knowledge on the relationship between the mediator and the outcome with binary exposure (Yin et al. (2024) ); estimate the direct and indirect effects using linear regression-based approach (VanderWeele (2015, ISBN:9780199325870)).

Fields of Study & Subjects

Advanced Causal Inference Techniques Statistical Methods in Epidemiology Statistical Methods and Bayesian Inference

Publication details

Publication date
13 January 2026
Document type
Dataset