useR! 2024

Summary tables are ubiquitous in scientific manuscripts reporting epidemiological and clinical studies. Table 1 often contains key demographic information about the study population, including the mean and standard deviation for continuous variables and frequency and proportion for categorical variables. Table 2 may present the association between the explanatory and outcome variables under investigation, and so on. Since there are endless ways (some more robust than others) to create analytical and summary tables in R, our research group wanted to define a workflow that could be adopted by colleagues of varying levels of proficiency in R to reproducibly create these tables from raw data. In this talk, I will share our approach in designing this workflow and what we discovered along the way. This will include a discussion on the current landscape of table-generating packages in R and how we overcame the limitations of existing software alongside other challenges (e.g., incorporating existing metadata). These strategies will not only be useful to researchers in epidemiology but also relevant for those in other health and social science disciplines.