An interactive web application for propensity score matching with R shiny; example of thrombophilia

Abstract

Aim: The aim of this study was to develop a new web-based R Shiny package that calculates propensity score using manyalgorithms such as logistic regression, machine learning, and performs matching analysis with balance evaluation. In addition, itwas aimed to explain the process of matching analysis on a real data set by comparing the number of live births between those withmethylenetetrahydrofolate reductase (MTHFR) homozygous mutations and those without mutations in women hospitalized due toabortion in the gynecology and obstetrics clinic.Material and Methods: The web-based application was developed using R shiny. The “matchIt” library was used for matchinganalysis and PS prediction. The “cobalt” library was used to evaluate balance and generate plots.Results: The abortion variable, which was statistically significantly different in the groups before matching (p=0.010), was similar inthe groups after matching (p=0.743). In addition, when the descriptive statistics and p values of the other variables were examined,it was seen that almost full balance was achieved after matching and the confounder variables were similar distributed in groups.After matching analysis, it was determined that the result variable “livebirths” did not show statistically significant difference in thegroups (p=0.864).Conclusion: In this study, we developed an interactive web application for matching analysis based on propensity score. It is thoughtthat this application will facilitate the studies of the researchers.