Checklist — Writing the Biostatistics write-up

A student-friendly checklist for a lab-report-style Biostatistics project write-up

In addition to this guideline, see

Guidelines for reporting on original research, whether an experiment or systematic reviews or meta-analysis are available, eg, PRISMA for systematic reviews. These are intended for the professionals, and while students would benefit from reviewing these documents, they are technical. Our biostatistics course goal is to report our research findings in an accessible way. Thus, we are using a lab-report style write-up framework. BI311 students are also expected to produce and share with the instructor a short video abstract of their completed work. This models the research effort engaged by graduate students, postdocs, and other research professionals. The video can also be included in the student’s portfolio, to be shared with future employers and graduate applications.

The lab-report guidelines for a biostatistics project follow. It is written with meta-analysis as the expected student project, but can be easily be adopted to report original experimental research.

Link to Checklist — Lab report write-up in Mike’s Genetics and Genomics Workbook

Write paragraphs, do not simply report a list of bullet-items. Include sub-headings as needed to improve reading and organization of the report.

  1. Introduction
    1. State the research question.
    2. Explain why the topic matters.
    3. One or two sentences on what a meta-analysis does (evidence synthesis).
  2. 2. Methods
    1. Search strategy
    2. Database used, search terms, date range.
    3. Inclusion and exclusion criteria
    4. Screening method
    5. How you decided which studies to include (abstract screening only).
    6. Number of included vs. excluded studies.
    7. Data extraction
    8. What variables you recorded (p-values, sample sizes, etc.).
    9. Statistical method
      • Describe Fisher’s method or your chosen technique.
    10. State any assumptions or simplifications.
  3. 3. Results
    1. Number of papers found.
    2. Number included.
    3. Number excluded and main reasons.
    4. Table of studies
    5. Citation, sample size, p-value, include/exclude, comments.
    6. Meta-analysis outcome
    7. Combined p-value (and effect size summary if done).
    8. Brief narrative of findings
      • “Of the N included studies, X reported significant results… Overall, the combined analysis suggests…”
  4. 4. Discussion
    1. Interpretation
      • What does the combined evidence say?
      • Strength of the evidence (strong? suggestive? mixed?).
      • Why are your results important?
      • Limitations
        1. Only abstracts, missing full-text details.
        2. P-values summarized rather than effect sizes.
        3. No assessment of publication bias.
        4. Limited to one database.
    2. Implications and next steps
    3. What future research or data would improve the analysis?
  5. 5. Conclusion
    1. A short 1-3 sentence summary answering your research question.
  6. G. Final Checks Before Turning In
    1. Inclusion/exclusion criteria listed clearly
    2. All included studies appear in the results table
    3. p-values are copied correctly
    4. if p-values imputed, correctly identified
    5. Combined p-value is computed correctly
    6. Methods and Results sections match the spreadsheet
    7. Strengths — what did you find and why is it important?
    8. Discussion acknowledges limitations clearly
    9. Writing is concise, student-friendly, and transparent

Notes:

This is a draft, written November 2025 by MD with assistance from generative AI, ChatGPT