Quantitative consulting service
Plan a sample size that matches the study you are actually running
Build a sample-size rationale around the actual design, estimand, uncertainty, clustering, attrition, and feasible recruitment.
Question→Design→Data→Model→Diagnostics→Interpretation
When this support is useful
Before collection, during protocol revision, or when a design change invalidates an earlier calculation.
- Which effect-size input is defensible?
- How do clustering or repeated measures change power?
- What does sensitivity analysis show?
How the decision is approached
The workflow starts with the research question and data-generating structure. Methods and software follow from that logic, with assumptions, alternatives, and failure modes recorded before conclusions are polished.
- Design-specific power models
- Simulation where appropriate
- Sensitivity analysis
What a defensible handover can include
Deliverables are agreed to fit the decision and the people who must review or continue the work. They are not a fixed bundle of software output.
- Power rationale
- Assumption record
- Sensitivity summary
Start with the decision
Discuss this statistical decision
Bring the research question, design, or existing output. A first review can identify the next statistical decision and the information needed to scope it.