Template
Plan how you will analyse your data | before you collect it.
A clear analysis plan locks down your variables and tests before fieldwork begins, so write-up is faster and reviewers have nothing to query.
Mini template
| Objective | Variables | Analysis | Software |
|---|---|---|---|
| Prevalence of outcome | Outcome (binary) | Proportion + 95% CI | Stata / R |
| Factors associated | Outcome + predictors | Logistic regression | Stata / R |
| Lived experience | IDI transcripts | Thematic analysis | NVivo / Dedoose |
Frequently asked
Questions researchers ask
- When should I write the analysis plan?
- Before you collect data. Writing it later forces you to fit analyses to whatever data you happen to have.
- What goes in an analysis plan?
- For each objective: the variables, the type of analysis, the test or model, the software, and how you will present the results.
- Do qualitative studies need an analysis plan?
- Yes: describe your coding approach (e.g. thematic, framework), who will code, and how you will check agreement.
- What software should I use?
- Stata, SPSS, R or Python for quantitative; NVivo, ATLAS.ti, Dedoose or even spreadsheets for qualitative. Pick what your supervisor can actually review.
- Will reviewers actually read it?
- Yes. A vague analysis plan is a common reason proposals are sent back from ethics or grant review.
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