Checklist

Experiment design & pre-registration checklist

Interactive checklist to design, document, and pre-register robust experiments. Captures the research question, hypothesis, design choices, randomization and blinding, sample-size and power details, analysis plan, success criteria, reproducibility and data-sharing plans, ethics and preregistration status, and sign-off — stored for repeatable organizational memory.

Interactive Tool

Experiment design & pre-registration checklist

Use this guided checklist to turn an idea into a clearly specified, reproducible experiment. Fill in decisions, calculations, and links so the team can interpret results, reproduce the work, and learn faster. Save the form to preserve protocol versioning and enable later review.

Short descriptive title for this experiment (used in records and preregistration).
State the concrete question you want to answer and the primary outcome measure used to decide success/failure.
Write the directional or non-directional hypothesis and the null hypothesis you will test.
Describe the statistical tests or models, transformations, covariates, and any pre-processing steps. Include software and version (e.g., R 4.2.1, package X vY).
Choose the overall experimental design.
Leave blank unless you selected 'Other' above.
Describe control(s), placebo, sham, baseline, or comparator condition(s).
Describe how randomization will be performed (e.g., computerized random number generator, block size, stratification factors).
E.g., sealed envelopes, central randomization service.
Who is blinded in the study?
List eligibility criteria that determine who/what will be enrolled or included.
List exclusions and reasons (safety, confounders, logistics).
Enter the number of experimental units planned. Consider per-group and total counts.
Report effect size, variance assumptions, alpha, power (1 - beta), one- or two-sided test, and formulas or software used. Paste command or link if available.
Common default is 0.05. Use decimal format (e.g., 0.05).
Specify adjustments for multiple tests (Bonferroni, FDR, pre-specified hierarchical testing, etc.).
If interim looks or stopping rules are planned, describe timing, criteria, and alpha spending methods. If none, state 'none planned'.
Describe who collects data, instruments, training, calibration, QA checks, and automated validation steps.
Include repository, folder structure, access controls, and backup strategy.
List metadata fields (dates, software versions, protocol version) and where protocol versions are stored (e.g., Git, lab notebook ID).
Specify how code, analysis scripts, and materials will be shared, and how environment reproducibility will be managed (containers, exact package versions).
Where will analysis code be stored (Git repo, DOI), license, and timing (upon publication, after embargo).
How will unique materials, reagents, or scripts be made available (MTAs, repositories)?
Human/animal/other regulated research: note approval ID or planned submission.
Approval number, committee, or expected submission date.
Record if you plan to pre-register and whether a registry entry exists.
Paste URL or registry identifier (e.g., OSF, ClinicalTrials.gov).
Define exactly how outcomes will be interpreted and any thresholds for decisions (including secondary outcomes).
List funders and any relevant COI that could influence interpretation or reporting.
Key dates: start, recruitment end, analysis, reporting, and expected publication or data release.
Name and role of person accountable for execution and sign-off.
Best contact for questions about the protocol.
Operational, ethical, safety, and statistical risks and how you will mitigate them.
Confirm you have completed or planned each item below.
Person who reviewed and approved this checklist.
YYYY-MM-DD
Links to protocols, analysis code, datasets, or external documents.
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