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If the analysis is complemented with the use of GitHub or a similar service, this enables full openness and transparency of our data analysis. The above points could be expanded or reduced depending on the researcher’s context, which may involve ethical issues of access to data, private funding in research, accessibility to the Internet or to the necessary tools and, of course, the time one is willing to invest in learning or training in these tools.Ī Basic Outline for Reproducibility of Data Analysisįor reproducibility of data analysis, it is certainly possible to use R and RStudio. To facilitate the learning for current and future generations.Contribute to the generation of further research related to our topic of study.Enable the application of the results if they are of great practical interest.To allow the revision, correction and improvement of the methods used in the study.This can be supported using cloud services., such as Dropbox or similar, and GitHub, which together would have the following advantages: To summarize, when talking about the reproducibility of a study, article, thesis, etc., three basic aspects should be covered: methods, results, and data analysis: This represents a problem, also in my opinion, since scientific work in any area should rely on full transparency of the process. That is, documentation is rarely, if ever, provided with the software information and the step-by-step procedure for generating the tables, figures and statistical analysis in the study, and access to the raw data (the unprocessed experimental data) is practically non-existent. In my opinion, when we talk about the reproducibility of a scientific study, we think more about the reproducibility of methods or results, omitting, most of the time, the reproducibility of the data analysis. Perhaps, with some luck, the information presented here will be useful to the reader in his or her daily work. These are things I wish I had known at the beginning of my master’s degree, and later in my PhD, and I have been learning and applying ever so imperfectly. This post contains several of my opinions on the topic, and most of the content is of a self-study and of reminder nature.