Q01
Long Text
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Power Analysis Parameter Intake Survey
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.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
36 questions · ~4 min
Q02
Long Text
What is the primary study area?
Q03
Multiple Choice
Which effect metric will the power analysis use?
Q04
Multiple Choice
What is the assumed distribution for the primary outcome?
Q05
Long Text
How many arms or groups does your study design include?
Q06
Long Text
What is the planned follow-up duration? (Please state the number and unit — e.g., '12 weeks', '6 months'.)
Q07
Long Text
Overall, how confident are you in the accuracy of the assumptions you provided in this survey?
Q08
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.
Q09
Long Text
Based on your responses in this survey, is there any additional context, assumptions, or constraints we should consider for your power analysis?
Q10
Multiple Choice
What is your primary role or discipline?
Q11
Long Text
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.
Q12
Multiple Choice
What is the primary outcome type?
Q13
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.)
Q14
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.)
Q15
Long Text
What is the planned allocation ratio across groups?
Q16
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%.)
Q17
Multiple Choice
What sources informed these estimates? (Select all that apply.)
Q18
Long Text
How many years of experience do you have with study design or analysis?
Q19
Long Text
What is the minimum detectable effect (MDE) you consider practically meaningful? (Use the same metric and units as your planned effect size.)
Q20
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.)
Q21
Long Text
What significance level (alpha) will you use? (e.g., 0.05, 0.01)
Q22
Long Text
The attrition rate you entered above is expressed per:
Q23
Long Text
Please provide any additional citations, datasets, or notes relevant to the assumptions you reported above.
Q24
Long Text
Which region are you primarily based in?
Q25
Long Text
What is the unit for the effect size? (e.g., mmHg, points; enter 'standardized' if unitless.)
Q26
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.)
Q27
Long Text
What is your target statistical power? (e.g., 0.80, 0.90)
Q28
Multiple Choice
How do you plan to handle missing data? (Select all that apply.)
Q29
Long Text
What type of organization do you primarily work in?
Q30
Multiple Choice
Will the primary hypothesis test be one-sided or two-sided?
Q31
Long Text
What country are you primarily based in? (Optional)
Q32
Multiple Choice
Is the design clustered or cluster-randomized?
Q33
Long Text
If your design is clustered, what is the assumed intra-class correlation (ICC)? (Enter a value between 0 and 1.)
Q34
Long Text
If your design is clustered, what is the expected average cluster size?
Q35
Multiple Choice
Does the study involve repeated measures or longitudinal outcomes?
Q36
Long Text
If your study has repeated measures, what is the assumed within-subject correlation (rho)? (Enter a value between 0 and 1.)
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
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Open this template in the editor. Every part is yours to change before the first respondent sees it.