Power Analysis Parameter Intake Survey

Welcome to the Power Analysis & Sample Size Planning Survey. This survey collects the assumptions and parameters needed to conduct a power or sample size analysis for your study. Your responses will be used solely to inform your analysis plan and will be kept confidential. There are no right or wrong answers — best estimates are perfectly acceptable. The survey takes approximately 8–12 minutes. Participation is voluntary, and you may stop at any time.

What is the primary study area?

• Biomedical / Clinical
• Public Health
• Social Science
• Education
• Economics
• Psychology / Behavioral
• Engineering
• Other

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

What is the planned effect size? (Enter the numeric value in your chosen metric — e.g., 0.3 for Cohen's d, 1.5 for an odds ratio.)

What is the minimum detectable effect (MDE) you consider practically meaningful? (Use the same metric and units as your planned effect size.)

What is the unit for the effect size? (e.g., mmHg, points; enter 'standardized' if unitless.)

What is the assumed distribution for the primary outcome?

• Normal
• Binomial
• Poisson
• Negative binomial
• Log-normal
• Exponential
• Weibull

If your primary outcome is continuous, what is the assumed standard deviation? (Enter the value in outcome units; leave blank if not applicable.)

If your primary outcome is binary, what is the expected control-group event rate? (Enter a proportion between 0 and 1; leave blank if not applicable.)

What are the source(s) for your variance or event-rate assumptions? (e.g., pilot data, literature, registry — please include citations or links where possible.)

How many arms or groups does your study design include?

• 1 (single-group)
• 2
• 3
• 4 or more

What is the planned allocation ratio across groups?

• 1:1
• 2:1
• 1:2
• 1:1:1
• Other

What significance level (alpha) will you use? (e.g., 0.05, 0.01)

What is your target statistical power? (e.g., 0.80, 0.90)

Will the primary hypothesis test be one-sided or two-sided?

• Two-sided
• One-sided

Is the design clustered or cluster-randomized?

• No
• Yes

If your design is clustered, what is the assumed intra-class correlation (ICC)? (Enter a value between 0 and 1.)

If your design is clustered, what is the expected average cluster size?

Does the study involve repeated measures or longitudinal outcomes?

• No
• Yes

If your study has repeated measures, what is the assumed within-subject correlation (rho)? (Enter a value between 0 and 1.)

What is the planned follow-up duration? (Please state the number and unit — e.g., '12 weeks', '6 months'.)

What is the expected attrition or loss-to-follow-up rate over the full analysis window? (Enter a proportion between 0 and 1 — e.g., 0.15 for 15%.)

The attrition rate you entered above is expressed per:

• Week
• Month
• Entire follow-up period

How do you plan to handle missing data? (Select all that apply.)

• Complete-case analysis
• Multiple imputation
• Maximum likelihood / mixed models
• Inverse probability weighting
• Last observation carried forward
• Other (please specify)

Overall, how confident are you in the accuracy of the assumptions you provided in this survey?

What sources informed these estimates? (Select all that apply.)

• Pilot data
• Prior RCT
• Observational dataset
• Systematic review / meta-analysis
• Registry / EMR
• Expert judgment
• Feasibility constraints

Please provide any additional citations, datasets, or notes relevant to the assumptions you reported above.

Thank you for the details you've provided so far. I'd like to ask a couple of follow-up questions to clarify any gaps in your study assumptions — particularly around your variance estimates, design trade-offs, or feasibility constraints.

Based on your responses in this survey, is there any additional context, assumptions, or constraints we should consider for your power analysis?

What is your primary role or 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?

• Less than 1 year
• 1–3 years
• 4–7 years
• 8–15 years
• 16+ years

Which region are you primarily based in?

• Africa
• Asia
• Europe
• North America
• South America
• Oceania
• Middle East
• Multiple / Other

What type of organization do you primarily work in?

• University / Academic
• Hospital / Health system
• Government
• Industry / Pharma
• Nonprofit / NGO
• Independent consultant
• Other

What country are you primarily based in? (Optional)

Thank you for completing this survey. Your responses will be used to tailor an appropriate power and sample size analysis plan for your study. If you have questions, please contact your study statistician or the research team.