BERDI Research Resources

Clinical researchers can now access and share professional development offerings and resources on the NIH-funded Development, Implementation, and AssessMent of Novel Training in Domain-Based Competencies (DIAMOND) Portal. DIAMOND is a collaborative discovery learning space for clinical research professionals and other members of research study teams. Training and assessment items included in the DIAMOND collection are searchable by competency domain and provide information and links to offerings for study teams.

• NIH study quality assessment guides
• Effective Public Health Practice Project. (1998). Quality Assessment Tool For Quantitative Studies. Hamilton, ON: Effective Public Health Practice Project.
• Ryan R, Hill S, Prictor M, McKenzie J; Cochrane Consumers and Communication Review Group. Study Quality Guide. May 2013
• STROBE: Strengthening the reporting of observational studies in epidemiology **

** We also find these checklists helpful when devising analytic plans, drafting manuscripts, and performing peer-review.

• Data Sets for Quantitative Research: Public Use Datasets: resources compiled by the University of Missouri 
• Finding Data Sets for the Health and Natural Sciences Resources: compiled by UNC
• NCHS Public-Use Data Files and Documentation
• Datasets and raw data: list of publicly available health datasets compiled by UC Berkeley 
• Open data repositories is a crowd-sourced list of publicly available health, medicine, and epidemiologic datasets free for use 
• #epitwitter’s favorite public use datasets (and another thread here)

Universities across the US have Biostatistics Epidemiology & Research Design (BERD) programs that offer training to clinical researchers. Some archive lectures, slides, and workshop material for public use:

• Brown University Advanced CTR YouTube channel, event recordings and webinars, and recent Biostatistics Core seminars
• Oregon Health & Science University archived seminars
• Boston University archived seminars
• Columbia University Irving Medical School YouTube channel

UCLA has an impressive collection of coding examples across statistical software that are typically well annotated.

• Materials from past workshops in Stata, SAS, R, and SPSS 

• Recordings from Oregon Health & Science University’s Biostatistics, Epidemiology, and Research Design (BERD) Program. Also available online are resources and exercises for the webinars below.
• “Getting started with R studio”:
  • September 24, 2019
  • February 19, 2020
• “Data wrangling in R”:
  • Part 1A (April 18, 2019)
  • Part 1B (April 18, 2019)
  • Part 2 (April 25, 2019)
• “Reproducible reports with R markdown”:
  • September 26, 2019
• “Data visualization with R & ggplot2”:
  • March 4, 2020
  • May 20, 2020

• Stata webinar archive
• Resources for learning stata

• Looking for an appropriate target journal for your manuscript and/or relevant articles to cite? You can paste your abstract – and even your full text – into Jane and click on "Find Journals," "Find Authors" or "Find Articles." Jane will then compare your text to millions of documents in PubMed to find the best matching journals, authors or articles.
• Cummings P, Rivara FP, Koepsell TD. Writing Informative Abstracts for Journal Articles. Arch Pediatr Adolesc Med. 2004;158(11):1086–1088. doi:10.1001/archpedi.158.11.1086
• Mensh B, Kording K (2017). Ten simple rules for structuring papers. PLoS Comput Biol 13(9): e1005619. https://doi.org/10.1371/journal.pcbi.1005619
• Bem D. Writing the empirical journal article.
• Lamott, Anne. Shitty First Drafts. Language Awareness: Readings for College Writers. Ed. by Paul Eschholz, Alfred Rosa, and Virginia Clark. 9th ed. Boston: Bedford/St. Martin’s, 2005: 93-96.
• Luby S, Southern D. The Pathway to Publishing: A Guide to Quantitative Writing in the Health Sciences. Last revised August 2017.

• Hayes-Larson E, Kezios KL, Mooney SJ, Lovasi G. Who is in this study, anyway? Guidelines for a useful Table 1. J Clin Epidemiol. 2019;114:125-132. doi:10.1016/j.jclinepi.2019.06.011
• Westreich D, Greenland S. The table 2 fallacy: presenting and interpreting confounder and modifier coefficients. Am J Epidemiol. 2013;177(4):292-298. doi:10.1093/aje/kws412
• Cummings P, Rivara FP. Reporting Statistical Information in Medical Journal Articles. Arch Pediatr Adolesc Med. 2003;157(4):321–324. doi:10.1001/archpedi.157.4.321

• Rivara FP, Christakis DA, Cummings P. Duplicate Publication. Arch Pediatr Adolesc Med. 2004;158(9):926. doi:10.1001/archpedi.158.9.926
• Cummings P, Rivara FP. Spin and Boasting in Research Articles. Arch Pediatr Adolesc Med. 2012;166(12):1099–1100. doi:10.1001/archpediatrics.2012.1461

• Rivara FP, Cummings P. Writing for Publication in Archives of Pediatrics & Adolescent Medicine. Arch Pediatr Adolesc Med. 2001;155(10):1090–1092. doi:10.1001/archpedi.155.10.1090
• Bennett DA, Brayne C, Feigin VL, et al. Development of the standards of reporting of neurological disorders (STROND) checklist: a guideline for the reporting of incidence and prevalence studies in neuroepidemiology. Eur J Epidemiol. 2015;30(7):569-576. doi:10.1007/s10654-015-0034-5
• Rothman KJ. Writing for epidemiology. Epidemiology. 1998;9(3):333-337. doi:10.1097/00001648-199805000-00019
• APA Publications and Communications Board Working Group on Journal Article Reporting Standards. Reporting standards for research in psychology: why do we need them? What might they be?. Am Psychol. 2008;63(9):839-851. doi:10.1037/0003-066X.63.9.839
• Vandenbroucke, Jan P.; von Elm, Erik; Altman, Douglas G.; Gøtzsche, Peter C.; Mulrow, Cynthia D.; Pocock, Stuart J.; Poole, Charles; Schlesselman, James J.; Egger, Matthias for the STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration. Epidemiology: November 2007 – Volume 18 – Issue 6 – p 805-835. doi: 10.1097/EDE.0b013e3181577511

• Cummings P, Rivara FP. Responding to Reviewers’ Comments on Submitted Articles. Arch Pediatr Adolesc Med. 2002;156(2):105–107. doi:10.1001/archpedi.156.2.105
• Althouse A. Reference collection to push back against “common statistical myths”

• In partnership with the OHSU BERD Core, Dr. Andrea has co-created and coordinates a seminar series titled “Antiracism in Data and Analysis.” Materials from previous sessions can be viewed here:
  • Session 1: Can Data Be Racist?
    
    Introductory Lecture | Discussion Article | Session Recording
  • Session 2: Reflection on Race & Ethnicity in Epidemiology
    
    Session Recording | Resources Part 1 | Resources Part 2
• Antiracism Resources for Epidemiologists & Public Health Researchers: Crowdsourced list of resources on critical histories of epidemiologic and public health research, research ethics and epidemiologic knowledge production, epidemiology for social justice, allyship/antiracism in epidemiologic research, subject matter, theoretical frameworks, methods, and data science and equity.
• "Health equity tourists": How white scholars are colonizing research on health disparities: An important commentary highlighting the ways in which racism is even embedded in the way we approach researching health disparities.
• Race & Medicine: A selection of articles from the New England Journal of Medicine on race and medicine, with implications for improving patient care, professional training, research, and public health.
• On Racism: A New Standard for Publishing on Racial Health Inequities. Health Affairs Blog, July 2, 2020. DOI: 10.1377/hblog20200630.939347
• Ward J.B., Gartner D.R., Keyes K.M., Fliss M.D., McClure E.S., Robinson W.R. How do we assess a racial disparity in health? Distribution, interaction, and interpretation in epidemiological studies. Ann Epidemiol. 2019;29:1-7. doi:10.1016/j.annepidem.2018.09.007

• Population Health Exchange (PHX): Update your population health skill set or deepen your understanding of the pressing public health issues of our time with these tools and resources.
• Columbia SPH keeps and updates great descriptions and additional resources regarding important and emerging population health techniques and the tensions that may arise in the selection and application of appropriate techniques. 
• EpiToDate is an effort to curate, catalog, annotate and share useful, interesting and relevant resources in epidemiology and allied fields in a compact easy-to-read format.