A structured intake instrument for statisticians and researchers to systematically document effect size, variance, design, and attrition assumptions needed to conduct power and sample size calculations.
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AI-Powered Questions
Intelligent follow-up questions based on responses
Automated Analysis
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Template Overview
36
Questions
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This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.
Sample Survey Items
Q1
Chat Message
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.
Q2
Dropdown
What is the primary study area?
Biomedical / Clinical
Public Health
Social Science
Education
Economics
Psychology / Behavioral
Engineering
Other
Q3
Multiple Choice
What is the primary outcome type?
Continuous
Binary / Proportion (0–1)
Count
Time-to-event (survival)
Ordinal
Other
Q4
Multiple Choice
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
Q5
Long Text
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.)
Max chars
Q6
Long Text
What is the minimum detectable effect (MDE) you consider practically meaningful? (Use the same metric and units as your planned effect size.)
Max chars
Q7
Long Text
What is the unit for the effect size? (e.g., mmHg, points; enter 'standardized' if unitless.)
Max chars
Q8
Multiple Choice
What is the assumed distribution for the primary outcome?
Normal
Binomial
Poisson
Negative binomial
Log-normal
Exponential
Weibull
Q9
Long Text
If your primary outcome is continuous, what is the assumed standard deviation? (Enter the value in outcome units; leave blank if not applicable.)
Max chars
Q10
Long Text
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.)
Max chars
Q11
Long Text
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.)
Max chars
Q12
Dropdown
How many arms or groups does your study design include?
1 (single-group)
2
3
4 or more
Q13
Dropdown
What is the planned allocation ratio across groups?
1:1
2:1
1:2
1:1:1
Other
Q14
Long Text
What significance level (alpha) will you use? (e.g., 0.05, 0.01)
Max chars
Q15
Long Text
What is your target statistical power? (e.g., 0.80, 0.90)
Max chars
Q16
Multiple Choice
Will the primary hypothesis test be one-sided or two-sided?
Two-sided
One-sided
Q17
Multiple Choice
Is the design clustered or cluster-randomized?
No
Yes
Q18
Long Text
If your design is clustered, what is the assumed intra-class correlation (ICC)? (Enter a value between 0 and 1.)
Max chars
Q19
Long Text
If your design is clustered, what is the expected average cluster size?
Max chars
Q20
Multiple Choice
Does the study involve repeated measures or longitudinal outcomes?
No
Yes
Q21
Long Text
If your study has repeated measures, what is the assumed within-subject correlation (rho)? (Enter a value between 0 and 1.)
Max chars
Q22
Long Text
What is the planned follow-up duration? (Please state the number and unit — e.g., '12 weeks', '6 months'.)
Max chars
Q23
Long Text
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%.)
Max chars
Q24
Dropdown
The attrition rate you entered above is expressed per:
Week
Month
Entire follow-up period
Q25
Multiple Choice
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)
Q26
Opinion Scale
Overall, how confident are you in the accuracy of the assumptions you provided in this survey?
Range: 1 – 7
Min: Not at all confidentMid: NeutralMax: Extremely confident
Q27
Multiple Choice
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
Q28
Long Text
Please provide any additional citations, datasets, or notes relevant to the assumptions you reported above.
Max chars
Q29
AI Interview
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.
AI InterviewLength: 3Personality: [Object Object]Mode: Fast
Reference questions: 7
Q30
Long Text
Based on your responses in this survey, is there any additional context, assumptions, or constraints we should consider for your power analysis?
Max chars
Q31
Multiple Choice
What is your primary role or discipline?
Biostatistician
Epidemiologist
Clinical researcher
Social scientist
Data analyst
Student / trainee
Other
Q32
Dropdown
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
Q33
Dropdown
Which region are you primarily based in?
Africa
Asia
Europe
North America
South America
Oceania
Middle East
Multiple / Other
Q34
Dropdown
What type of organization do you primarily work in?
University / Academic
Hospital / Health system
Government
Industry / Pharma
Nonprofit / NGO
Independent consultant
Other
Q35
Long Text
What country are you primarily based in? (Optional)
Max chars
Q36
Chat Message
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.
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