# Description This repository includes R code to run all of the analysis for the paper: _Effect of biannual azithromycin distribution on antibody responses to malaria, bacterial, and protozoan pathogens in Niger_ Arzika, A. M., Maliki, R., Goodhew, E. B., Rogier, E., Priest, J. W., Lebas, E., O’Brien, K. S., Le, V., Oldenburg, C. E., Doan, T., Porco, T. C., Keenan, J. D., Lietman, T. M., Martin, D. L., Arnold, B. F. & MORDOR-Niger Study Group. _Nat. Commun._ 13, 976 (2022). https://pubmed.ncbi.nlm.nih.gov/35190534/ https://www.nature.com/articles/s41467-022-28565-5 Should you have any questions about the files in this repository, please contact Ben Arnold at UCSF (firstname.lastname@example.org). This OSF repository has a component that mirrors the source code, which was developed through GitHub: https://github.com/proctor-ucsf/mordor-antibody To run the scripts: (1) clone the GitHub repo; (2) create a data subdirectory and copy the two datasets from the OSF project into it; (3) then, create a figures subdirectory to store output. All of the analysis scripts should run smoothly (scripts 03-xx to 16-xx). The first two data processing scripts will not run because they read in our internal datasets with PII. We have included them for transparency and completeness. Should you have any questions about the files in this repository, please contact Ben Arnold at UCSF (email@example.com). ## Contents **Statistical Analysis Plan**: Includes the study's registered pre-analysis plan for antibody-based measures of infection. **Data**: Analysis datasets used to run all analyses. **Scripts**: R scripts used to run the analysis **Computational Notebooks**: HTML notebooks created by the R markdown (`.Rmd`) files in the Scripts component, updated to their current version (currently release v3 on GitHub: https://github.com/proctor-ucsf/mordor-antibody/releases/tag/v3) **Additional Resources** Any additional resources and documentation for the analysis (e.g., trial CONSORT checklist).