Open-Source Software for Causal Transportability Analysis

Randomized clinical trials (RCTs) are considered the gold standard due to their excellent internal validity results and are a vital tool for evidence-informed global health policymaking. However, the external validity, which results from the uniqueness of low- and middle-income countries (LMICs) in healthcare, culture, and demography, significantly hampers the value of RCTs in these regions. This dilemma can be addressed with a causal inference framework called Transportability analysis, which accounts for effect modifiers that differ between the study population and target population and aim to achieve the extension (transportation) of RCT findings.
Our primary objective is to develop a software package based on R language to adopt a subgroup analysis method called Network meta-interpolation (NMI) to impute the missing values in the cells for the original study and/or target study with aggregate data. With the enriched data, we will consider various indirect treatment comparisons (ITC) to assess effect modifications in meta-analyses of aggregate data.
Our secondary objective is to complete an interactive web interface so future researchers and policymakers can use the proposed model easily during decision-making.

Faculty Supervisor:

Haolun Shi

Student:

Partner:

Core Clinical Sciences

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program: