JASA Reproducibility Awardees

The JASA Editorial Board and Associate Editors for Reproducibility would like to congratulate the winners on their exceptional contributions to computational reproducibility within the statistical field! 🏅

These awards are selected by the JASA Associate Editors of Reproducibility (AERs) and a description of the JASA Reproducibility Award is described here.

2024

• Yabo Niu, Yang Ni, Debdeep Pati, Bani K. Mallick. (2023). Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data, Journal of the American Statistical Association, DOI: 10.1080/01621459.2023.2233744

  • Code to reproduce results: https://www.tandfonline.com/doi/suppl/10.1080/01621459.2023.2233744?scroll=top

• Stéphane Guerrier, Christoph Kuzmics, Maria-Pia Victoria-Feser. (2024). Assessing COVID-19 Prevalence in Austria with Infection Surveys and Case Count Data as Auxiliary Information, Journal of the American Statistical Association, DOI: 10.1080/01621459.2024.2313790

  • R software package: https://github.com/stephaneguerrier/pempi
  • Code to reproduce results: https://stephaneguerrier.github.io/pempi/articles/reproducibility.html

2023

• Lucy L. Gao, Jacob Bien, Daniela Witten (2022). Selective Inference for Hierarchical Clustering, Journal of the American Statistical Association, DOI: 10.1080/01621459.2022.2116331

  • R software package: http://lucylgao.com/clusterpval
  • Code to reproduce results: https://github.com/lucylgao/clusterpval-experiments

• Cecilia Balocchi, Sameer K. Deshpande, Edward I. George, Shane T. Jensen (2023). Crime in Philadelphia: Bayesian Clustering with Particle Optimization, Journal of the American Statistical Association, DOI: 10.1080/01621459.2022.2156348

  • R software package: https://github.com/cecilia-balocchi/particle-optimization/tree/master/PARTOPT
  • Code to reproduce results: https://github.com/cecilia-balocchi/particle-optimization