Malcomb et al. (2014) Study Reproduction

During the reproduction of the paper, Vulnerability modeling for sub-Saharan Africa: An operationalized approach in Malawi by Malcolm et al., I add a zonal statistic. Employing the aggregate function from the stars R package, climate vulnerability raster data is aggregated into Traditional Authorities (TA) vectors, an administrative unit in Malawi. Policies and resources are set and allocated by administrative districts. Having climate vulnerability attached to TAs provides stakeholders and policymakers with an additional layer of data to make informed decisions about climate vulnerability in Malawi.

The challenges of reproducing studies continued to crystalize while I worked on the Malcomb et al. reproduction. When fully engaged, a paper’s methods, even clearly described, can prove unclear, vague, and, at points, baffling. The study is built upon poor data. We attempted to follow the original study’s methods; however, at certain points, their methods proved unclear. I learned more about the impacts misused and poor quality data can have on an analysis. The context and methods of how data is collected greatly impacts the validity of one’s study. As the maxim goes, “Garbage in, garbage out.”

Please follow this link to the entire reproduction study.

Please follow this link to the reproduction study’s Github repository.