tableone - Create 'Table 1' to Describe Baseline Characteristics with or without Propensity Score Weights

Creates 'Table 1', i.e., description of baseline patient characteristics, which is essential in every medical research. Supports both continuous and categorical variables, as well as p-values and standardized mean differences. Weighted data are supported via the 'survey' package.

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baseline-characteristicsdescriptive-statisticsstatistics

13.81 score 235 stars 12 dependents 3.5k scripts 24k downloads

regmedint - Regression-Based Causal Mediation Analysis with Interaction and Effect Modification Terms

This is an extension of the regression-based causal mediation analysis first proposed by Valeri and VanderWeele (2013) <doi:10.1037/a0031034> and Valeri and VanderWeele (2015) <doi:10.1097/EDE.0000000000000253>). It supports including effect measure modification by covariates(treatment-covariate and mediator-covariate product terms in mediator and outcome regression models) as proposed by Li et al (2023) <doi:10.1097/EDE.0000000000001643>. It also accommodates the original 'SAS' macro and 'PROC CAUSALMED' procedure in 'SAS' when there is no effect measure modification. Linear and logistic models are supported for the mediator model. Linear, logistic, loglinear, Poisson, negative binomial, Cox, and accelerated failure time (exponential and Weibull) models are supported for the outcome model.

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causal-inferencemediation-analysis

7.33 score 36 stars 50 scripts 960 downloads