01 · DELIVERABLE
Variable and subgroup missingness summary
Confirm the exact format, accountable reviewer and acceptance criteria in the written scope before work begins.
Researchers facing incomplete datasets · Worldwide online
Missing data in research
Separate why data are missing from how an analysis method handles them.
Check My Dataset →Inspect real dataset evidenceTHE BUYER PROBLEM
Resolve the decision behind the request.
Deleting every incomplete row can change the analysis population and produce biased or imprecise conclusions.
HOW THE WORK MOVES
Scope first. Traceable decisions throughout.
- Separate skipped, refused and unknown values
- Describe patterns and predictors
- Assess plausible mechanisms
- Review candidate analysis and sensitivity checks
Professional delivery uses the existing canonical project and case workflow. Independent QA and release approval are distinct decisions; unresolved findings remain visible.
What the agreed scope can deliver
02 · DELIVERABLE
Missing-code and eligibility decisions
Confirm the exact format, accountable reviewer and acceptance criteria in the written scope before work begins.
03 · DELIVERABLE
Sensitivity-analysis planning questions
Confirm the exact format, accountable reviewer and acceptance criteria in the written scope before work begins.
Methods, assumptions and boundaries
MCAR, MAR and MNAR cannot generally be established from a missingness percentage. Imputation requires design and model review.
Source values are preserved; changes require documented reasons. Analysis needs a defined outcome, population, design and eligible records. Review may withhold an unsupported test or conclusion.
Read the RMA methodology →Start with context. Transfer data privately.
The public fit check asks for objectives, stage and constraints. Do not paste participant names, health records, passwords or connector tokens. Access, permitted data, retention and export/deletion arrangements are confirmed before private transfer.
Review data-handling boundaries →Is this a fit?
For researchers facing incomplete datasets who can explain the intended decision, provide authorised evidence and accept transparent limitations.
Outside scope: fabricated data, guaranteed significance, thesis ghostwriting, clinical decision-making or claims of regulatory certification.
Before you start
What does the first enquiry commit me to?
Nothing is charged through the fit-check form. RMA reviews scope and confirms deliverables, exclusions, timing and price in writing.
Will I need a personal or organisation workspace?
Choose personal research or an organisation project during intake. The same RMA account can participate in both. A professional service is linked to the canonical case; it does not create a separate portal.
Can you guarantee an outcome or approval?
No. Findings depend on the source data and design. QA checks the agreed evidence and cannot guarantee significance, graduation, grant funding or publication.
Prepare a stronger brief.
Research operations overview · Free research tools · Organisation product tour
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