The Sample-Size Justification Kit

What it's for

Walk in asking how many participants you need. Walk out with a computed number, the record behind it, and a justification paragraph that answers the questions before they are asked.

What's inside

1. Name the decision — Pin down the four parameters, the analysis you are powering and what your programme actually requires.
2. Choose the type of analysis — A priori, sensitivity, compromise — decided by two questions, with the observed-power trap explained.
3. Design → test → inputs — A map from twelve common designs to the test and the exact inputs that test needs.
4. Set α, power and tails — Each one justified, with a multiplicity planner for studies that test more than one hypothesis.
5. Source the effect size — The source hierarchy, a candidate table and the quality questions reviewers ask about every estimate.
6. Convert, choose, stress-test — Metric conversions, the smallest effect that would matter, and a low / likely / high sensitivity range.
7. Run it and log every setting — The five-step routine, the output checks, and the settings log your appendix needs.
8. Means: t-tests and ANOVA — Inputs by design, the ones people miss, and a sanity check on the number you get back.
9. Associations, regression, proportions — Correlation, regression, chi-square and logistic designs, where the effect size is defined differently again.
10. Clustered and advanced designs — Design effect and intraclass correlation, and where to go when the standard software stops being enough.
11. Inflate to a recruitment target — Attrition, allocation and clustering applied in order, then the eligibility funnel.
12. Can you actually recruit it? — The feasibility check, and the options when the gap does not close.
13. Qualitative and mixed rationale — Information power, a saturation stopping rule and a monitoring log — for the strands no power analysis fits.
14. Write it and defend it — Paragraph skeletons for every case, a reporting-completeness check and the questions to rehearse.

Swipe cards — the rules, formulas and phrasings worth keeping beside you, on one page to cut out.

The Calculator & Log (Excel / Google Sheets)

• Effect Size: candidates in one place, converted between d, r, η² and f
• Sample Size: attrition, allocation and clustering inflation, through to the recruitment target
• Settings Log: one row per calculation — the reproducible appendix record
• Feasibility: the per-week rate you need against the rate you can achieve, with a verdict
• Reporting: the ten elements of a complete justification, with a counter for what is missing

Look inside

Low-resolution, watermarked previews of four of the 18 pages.

Who it's for

• Master's and doctoral students writing the sample-size section of a proposal, ethics application or grant.
• Anyone whose committee has asked “how did you arrive at that number?” and wants the answer in writing.

It is not a power calculator and it does not compute power for you — it is the decision, sourcing and reporting layer around whichever tool you use.

From the author

Companion to The Sample Size & Power Analysis Workbook (Mastering Research Series), by Dr. Rafiq Muhammad, MD, PhD.

The kit is the worksheet layer; the workbook adds the method, the worked examples and the field notes behind each step.

Licence and refunds

One purchaser, personal academic use: print and annotate freely; please don't share, resell or upload the files to shared drives or course sites. Refund on request within 14 days if the files cannot be downloaded or opened. Full terms.

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Other kits

• Scoping Review Protocol — a search log, screening decisions, a charting form and the flow numbers.
• Data Cleaning & Codebook — a cleaning log, a missing-data record and a codebook for an analysis-ready dataset.
• Abstract, Title & Keyword — a word budget, title scoring and a keyword map for the 250 words that matter.

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