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Reproducibility, Replicability, and Open Science Practices in the Geographical Sciences /
A Framework for Moving Beyond Computational Reproducibility: Lessons from Three Reproductions of Geographical Analyses of COVID19
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Description: Supplementary files for manuscript https://osf.io/preprints/metaarxiv/7jqtv/ include three project components, one for each reproduction study
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Components
Reproduction of Mollalo et al 2020
Mollalo et al. (2020) investigated county-level variations of COVID-19 incidence across the continental United States using spatial lag and spatial er...
Reproduction of Vijayan et al 2020
Vijayan et al. (2021) examined whether spatial patterns existed in SARS-CoV-2 age-adjusted testing rates, age-adjusted diagnosis rates, and crude posi...
Reproduction of Saffary et al 2020
The original study is one of the first spatial statistical analyses of of COVID-19 in the United States. A main contribution of the study is to provid...
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