A Reflection on My Contributions to the Chakraborty Reproduction Study
Coming into this reproduction study, I felt a little apprehensive as I scrolled through the lines of code. I wasn’t sure exactly how I could contribute, but by the end of the study I felt much more confident about what I could do. On a basic level, I learned how to navigate a study translated entirely into R markdown; I ran blocks of code and looked at the various deviations that had already taken place in order to improve the study. From this, I gained insight into the possibilities of what I could do in a reproduction study, which I can apply to later studies. For example, just as new visualizations can improve a study, so too can cleaning up a table so its easier to read and fixing other more minor issues.
Specifically for teaching purposes, I felt it was really useful to be given a list of possible things that we could fix. For example, knowing that we needed to make smaller changes, from fixing a table to removing a missing parameter to fix a choropleth map, were good first steps. It was a bit overhwelming to look at all the code for a reproduction study coming into lab, but breaking down smaller steps to contributing were really helpful. However, something that I found a little frusterating was that I continually had to run and rerun several blocks of code in order to load all the data with all the correct attributes and modifications if I was interested in investigating something in the middle of the study. It was very tedious and time-consuming to run several preceding code blocks to load data I needed for one specific part of the study I was interested in later on.
References
Chakraborty, J. 2021. Social inequities in the distribution of COVID-19: An intra-categorical analysis of people with disabilities in the U.S. Disability and Health Journal 14 (1):101007. DOI: 10.1016/j.dhjo.2020.101007.