RESEARCH METRICS AFRICA

Researchers and organisations with an existing dataset · Worldwide online

Research data quality audit

Find structural and analytical risks before relying on your results.

Request Data Quality Audit →Inspect real dataset evidence

THE BUYER PROBLEM

Resolve the decision behind the request.

Missing codes, duplicate IDs and contradictory responses can survive a tidy spreadsheet and undermine the analysis.

HOW THE WORK MOVES

Scope first. Traceable decisions throughout.

  1. Define row unit and expected rules
  2. Screen a versioned source
  3. Review flags against the instrument
  4. Approve decisions and readiness

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

01 · DELIVERABLE

Completeness, duplicate, range and logic issue register

Confirm the exact format, accountable reviewer and acceptance criteria in the written scope before work begins.

02 · DELIVERABLE

Source-preserving cleaning decision log

Confirm the exact format, accountable reviewer and acceptance criteria in the written scope before work begins.

03 · DELIVERABLE

Analysis readiness memo with unresolved issues

Confirm the exact format, accountable reviewer and acceptance criteria in the written scope before work begins.

Methods, assumptions and boundaries

A flagged record is a review signal. Absence of flags does not prove correctness, representativeness or authenticity.

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 and organisations with an existing dataset 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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