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A method for estimating causal effects from heterogeneous clinical trials without a common control group using sequential regression and simulation: an individual participant data meta-analysis and validation study.

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Sequential Regression and Simulation

This repository provides code used in our paper "A method for estimating causal effects from heterogeneous clinical trials without a common control group using sequential regression and simulation: an individual participant data meta-analysis and validation study".

It includes files used to aggregate and harmonize individual participant data from 9 randomized controlled trials (Data Preparation), and files used for a meta-analysis (Modeling Process).

The raw data are owned by the trial sponsors. The data may be accessed for reproduction and extension of this work following an application on the YODA and Vivli platforms and execution of a data use agreement.

Requirements

Programming was performed in the R language (4.2.2), using the packages dplyr, lme4, lmerTest, data.table, ggplot2, ggpubr, sjstats, patchwork, and gridExtra.

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A method for estimating causal effects from heterogeneous clinical trials without a common control group using sequential regression and simulation: an individual participant data meta-analysis and validation study.

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