Reproducible research on github
Budget: $30 – $250 USD
I'm looking for a freelancer to help me with a reproducible research project on GitHub. The project will involve utilizing the programming language R and will involve only one version to be tested. Data sources for the project will be open-source APIs. This project is an important part of my overall goal of developing efficient models to analyze complex datasets. The project requires a detailed report on the execution of the tests as well as a proof of reproducible of the project’s outcome. In order to successfully complete the project, the freelancer must be familiar with the GitHub platform and have a comprehensive understanding of the chosen programming language (R) and its associated libraries.
1) Take an econometric / statistical analysis (e.g. from your bachelor thesis or Kaggle):
– Translate the codes to a different programming language (e.g. R to Python or Stata to R, etc.)*
– Reproduce the results.
– Pick a way to improve the study or update the data** or perform a robustness check and do it.
– Discuss the findings, potential problems, inconsistencies and conclusions.
* you should try exploiting the advantages and functions of the ‘new’ language
** data update can include: collecting new survey data (not many), using newer datasets, etc.
2) Take a published (in a peer-reviewed journal) research paper with no code attached. Reproduce its (main) findings. Report on the problems along the way.
3) Take a simple meta-analysis study (examples below). Then do the following:
– Reproduce the obtained results using the reported sample of studies.
– Add 2-5 newer studies, preferably using the selection process reported in the original study.
– Replicate the results with the extended sample.
– Describe your findings and discuss them.
1) Take an econometric / statistical analysis (e.g. from your bachelor thesis or Kaggle):
– Translate the codes to a different programming language (e.g. R to Python or Stata to R, etc.)*
– Reproduce the results.
– Pick a way to improve the study or update the data** or perform a robustness check and do it.
– Discuss the findings, potential problems, inconsistencies and conclusions.
* you should try exploiting the advantages and functions of the ‘new’ language
** data update can include: collecting new survey data (not many), using newer datasets, etc.
2) Take a published (in a peer-reviewed journal) research paper with no code attached. Reproduce its (main) findings. Report on the problems along the way.
3) Take a simple meta-analysis study (examples below). Then do the following:
– Reproduce the obtained results using the reported sample of studies.
– Add 2-5 newer studies, preferably using the selection process reported in the original study.
– Replicate the results with the extended sample.
– Describe your findings and discuss them.