Literature DB >> 33467923

Reproducible Research: A Retrospective.

Roger D Peng1, Stephanie C Hicks1.   

Abstract

Advances in computing technology have spurred two extraordinary phenomena in science: large-scale and high-throughput data collection coupled with the creation and implementation of complex statistical algorithms for data analysis. These two phenomena have brought about tremendous advances in scientific discovery but have raised two serious concerns. The complexity of modern data analyses raises questions about the reproducibility of the analyses, meaning the ability of independent analysts to recreate the results claimed by the original authors using the original data and analysis techniques. Reproducibility is typically thwarted by a lack of availability of the original data and computer code. A more general concern is the replicability of scientific findings, which concerns the frequency with which scientific claims are confirmed by completely independent investigations. Although reproducibility and replicability are related, they focus on different aspects of scientific progress. In this review, we discuss the origins of reproducible research, characterize the current status of reproducibility in public health research, and connect reproducibility to current concerns about the replicability of scientific findings. Finally, we describe a path forward for improving both the reproducibility and replicability of public health research in the future.

Keywords:  data analysis; replicability; reproducibility

Year:  2021        PMID: 33467923     DOI: 10.1146/annurev-publhealth-012420-105110

Source DB:  PubMed          Journal:  Annu Rev Public Health        ISSN: 0163-7525            Impact factor:   21.981


  7 in total

1.  BioVisReport: A Markdown-based lightweight website builder for reproducible and interactive visualization of results from peer-reviewed publications.

Authors:  Jingcheng Yang; Yaqing Liu; Jun Shang; Yechao Huang; Ying Yu; Zhihui Li; Leming Shi; Zihan Ran
Journal:  Comput Struct Biotechnol J       Date:  2022-06-08       Impact factor: 6.155

2.  FA-nf: A Functional Annotation Pipeline for Proteins from Non-Model Organisms Implemented in Nextflow.

Authors:  Anna Vlasova; Toni Hermoso Pulido; Francisco Camara; Julia Ponomarenko; Roderic Guigó
Journal:  Genes (Basel)       Date:  2021-10-19       Impact factor: 4.096

3.  An Open-Access Data Platform: Global Nutrition and Health Atlas (GNHA).

Authors:  Bingjie Zhou; Shiwei Liang; Kyle M Monahan; Naglaa El-Abbadi; Melissa S Cruz; Yutong Chen; Annie DeVane; Julia Reedy; Jianyi Zhang; Iaroslava Semenova; Ivan Montoliu; Dariush Mozaffarian; Dantong Wang; Elena N Naumova
Journal:  Curr Dev Nutr       Date:  2022-03-11

4.  A simple kit to use computational notebooks for more openness, reproducibility, and productivity in research.

Authors:  Ludmilla Figueiredo; Cédric Scherer; Juliano Sarmento Cabral
Journal:  PLoS Comput Biol       Date:  2022-09-15       Impact factor: 4.779

5.  Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan.

Authors:  Sara Gonzales; Matthew B Carson; Kristi Holmes
Journal:  PLoS Comput Biol       Date:  2022-08-03       Impact factor: 4.779

Review 6.  Objectively measuring the association between the built environment and physical activity: a systematic review and reporting framework.

Authors:  Francesca L Pontin; Victoria L Jenneson; Michelle A Morris; Graham P Clarke; Nik M Lomax
Journal:  Int J Behav Nutr Phys Act       Date:  2022-09-14       Impact factor: 8.915

7.  Success4life Youth Empowerment for Promoting Well-being and Boosting Mental Health: Protocol for an Experimental Study.

Authors:  Sajita Setia; Daniel Furtner; Mounir Bendahmane; Michelle Tichy
Journal:  JMIR Res Protoc       Date:  2022-09-14
  7 in total

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