What is the primary outcome type?
- Continuous
- Binary/Proportion (0–1)
- Count
- Time-to-event (survival)
- Ordinal
- Other
Which effect metric will the power analysis use?
- Mean difference
- Standardized mean difference (Cohen's d)
- Odds ratio
- Risk ratio
- Risk difference
- Hazard ratio
- Rate ratio
- Correlation coefficient
- Change-score difference
Planned effect size (enter value in the chosen metric; e.g., 0.3 for d, 1.5 for a ratio)
Minimal detectable change (MDC/MDE) considered meaningful (use the same metric/units as the planned effect)
Unit for the effect (e.g., mmHg, points); enter 'standardized' if unitless
Max 100 chars
Assumed distribution for the primary outcome
- Normal
- Binomial
- Poisson
- Negative binomial
- Log-normal
- Exponential
- Weibull
Assumed standard deviation (if continuous outcome; in outcome units)
Expected control-group event rate/proportion (if binary; enter 0–1)
Source(s) for variance/event-rate assumptions (e.g., pilot data, literature, registry), including citations or links
Max 600 chars
Significance level (alpha; e.g., 0.05)
Target power (e.g., 0.80)
Is the design clustered/cluster-randomized?
Intra-class correlation (ICC), if clustered (enter 0–1)
Average cluster size, if clustered
Are there repeated measures/longitudinal outcomes?
Within-subject correlation (rho), if repeated measures (enter 0–1)
Planned follow-up duration (in weeks)
Expected attrition/loss-to-follow-up proportion over the analysis window (enter 0–1)
Attrition rate is expressed per:
Planned handling of missing data (select all that apply)
- Complete-case analysis
- Multiple imputation
- Maximum likelihood/mixed models
- Inverse probability weighting
- Last observation carried forward
How confident are you in these assumptions?
What informed these estimates? (select all that apply)
- Pilot data
- Prior RCT
- Observational dataset
- Systematic review/meta-analysis
- Registry/EMR
- Expert judgment
- Feasibility constraints
Citations, datasets, or notes relevant to these assumptions
Max 600 chars
Attention check: To confirm you are reading carefully, please select "I am paying attention."
- I am paying attention
- I am not paying attention
What is your primary role/discipline?
- Biostatistician
- Epidemiologist
- Clinical researcher
- Social scientist
- Data analyst
- Student/trainee
- Other
How many years of experience do you have with study design or analysis?
Which region are you primarily based in?
What type of organization do you primarily work in?
Country (optional)
Max 100 chars
Any additional context, assumptions, or constraints we should consider?
Max 600 chars
Welcome! This brief survey collects assumptions needed to plan a power/sample size analysis. Please answer as precisely as you can; best estimates are fine.
AI Interview: 2 Follow-up Questions on your study assumptions
Thank you for completing the survey. Your responses will help tailor an appropriate power/sample size plan.