Organisations & research teams
From field data to reviewed reporting.
For NGO, M&E, consultancy and institutional teams managing survey quality, project access and evidence delivery.
Explore Organisation Workspace →Discuss your organisation’s fit →DATA ANALYSIS · BIOSTATISTICS · NGO DATA QUALITY
Trust the data
behind every decision.
Kenya-based, worldwide online support from proposal design and SPSS, R or Excel analysis to Kobo/ODK quality audits, clean datasets and decision-ready reports.
Worldwide remote deliveryPrivate project workspacesAuditable cleaning & reporting
Kenya-based · Working worldwide
Research operations. Defensible evidence.
Research Metrics Africa is a research operations and analytics platform for researchers and organisations—combining research data quality, statistical planning and analysis, reproducibility, independent QA and controlled reporting in one accountable workflow.
PhD & independent researchers
Methods you can explain and defend.
Plan your study, review data, choose suitable methods and document analysis with support that respects your institution’s rules.
Explore researcher support →Find the right research support →A dataset that needs attention
Establish what the data can support.
Review missingness, coding, logic and the connection between your objectives, variables and proposed analysis.
Explore a data-quality audit →Request an audit fit check →See the research operations platformAlready working with RMA? Open Workspace
Real work · Clear limitations
505 catalogue records. Findings you can inspect.
An antimicrobial catalogue screen documented 2,598 missing cells, nine affected records and no potential duplicate groups in that run. Revised work documented reference comparisons and controlled QA resubmission.
The revision was not final QA or release authorisation. Original source provenance was not fully established; no clinical-use conclusions are supported. This public case shares RMA-generated aggregates and workflow evidence.
Read the case study and provenance limits →An accountable delivery path
Know what happens next.
- Clarify the fit. Start with public proof, a tool or a scope conversation.
- Agree the work. Record inputs, exclusions, responsibilities and deliverables.
- Work privately. Use the appropriate Personal or Organisation Workspace.
- Review before release. Keep analysis, independent QA and controlled delivery accountable.
A useful place to start
Make your next research decision with context.
No thesis ghostwriting, fabricated data or guaranteed significance. Public enquiries collect context; sensitive files belong in the agreed private project channel.
NGO data operations
From Kobo or ODK to a dataset your team can defend.
Connect live field data or upload it privately, validate structure before processing, review dataset-aware QA signals, document cleaning decisions and deliver an approved analysis-ready copy.
Live Kobo + ODKPrivate uploadsAudit-ready outputs
Kenya-based · Working worldwide online
Remote statistical support
with a visible method.
Researchers and public-health teams in the USA, UK, Canada, Australia and beyond can access documented SPSS, R and Excel analysis without a black-box handover. We agree time-zone overlap, privacy, deliverables and a USD or GBP quote before work begins.
What we do
One auditable path from field submission to final report.
Start with a dataset audit, pilot one live project, or let us operate the full quality and reporting cycle with your approved team.
01◎
Dataset Quality Audit
Find missingness, duplicates, invalid codes, logic failures and reporting risks before programme data reaches a donor or management decision.
KSh 15k–30k · Defined issue register↘02↗
Kobo/ODK Field Operations Pilot
Connect one active project, monitor live submissions, review QA signals and deliver a traceable cleaned dataset without overwriting the source.
KSh 50k–80k · One active project↘03◫
Monthly NGO Support
Run secure intake, QA, cleaning, review, analysis and reporting as a managed or hybrid data-operations workflow.
Custom scope · Managed or hybrid↘04Σ
Survey Data Cleaning & Analysis
Prepare analysis-ready Excel, CSV or SPSS files, choose suitable methods and report results with assumptions and limitations intact.
R · SPSS · Excel · CSV↘05◇
NGO-grade Data Governance
Use role-based access, private uploads, project isolation, secure downloads, audit trails, retention controls and de-identified public outputs.
Owner · Analyst · Client↘06⌁
Transparent Methods & Proof
Inspect a synthetic end-to-end audit example showing review signals, withheld analysis, corrective actions and clear evidence limits.
Case study · Sample audit PDF↘01
Dataset Quality AuditKSh 15k–30k · Defined issue register
↗02Kobo/ODK Field Operations PilotKSh 50k–80k · One active project
↗03Monthly NGO SupportCustom scope · Managed or hybrid
↗04Survey Data Cleaning & AnalysisR · SPSS · Excel · CSV
↗05NGO-grade Data GovernanceOwner · Analyst · Client
↗06Transparent Methods & ProofCase study · Sample audit PDF
↗BOOKYour situation needs a closer look?Choose a session and tell me what is going on
→Research capability
Good research should survive hard questions.
This is where I unpack how a study moves from a useful question to defensible methods, trustworthy data and a conclusion that does not overclaim.
Research questions & study design
A broad topic is not yet a study. This section shows how to narrow the question, define what can be measured and choose a design that can support the answer.
Statistical & biostatistical analysis
The goal is not the fanciest model. It is an analysis that fits the question, respects the data, checks its assumptions and explains uncertainty without hiding it.
Field research & data quality
Fieldwork is where tidy protocols meet real conditions. I focus on questions people understand, digital checks that help, and records you can trace without compromising participants.
Scientific communication & presentations
A result is not useful if the audience cannot follow the reasoning. Here I work on charts, reports and presentations that stay clear without making the evidence sound stronger than it is.
Our approach
We start with the real decision, document the method, check the data and communicate conclusions without making the evidence sound stronger than it is.
Discuss your study ↗Inside the research desk
See how each research decision affects the next.
I’ve organised the guides around the questions students actually meet—from framing a study to explaining what the results really mean.
Work on the shelf
Projects worth showing,
including the unfinished thinking.
This library documents the methods, working outputs and evidence limits behind our research and data work.
01Learning resource
Statistical analysis basics
A practical path from population and variable types to test selection, regression, power and responsible interpretation.
New guideOpen the statistics primer ↗02Presentation shelf
Methods, evidence & the thinking behind them
I’ll publish selected class presentations and methods explainers here as the work is ready to stand on its own.
First uploads in preparationExplore literature review ↗03Analysis shelf
Data work, code & what I learned
Selected analyses, visual summaries and code-backed explorations—with the limitations left in, not edited away.
Work in progressOpen the biostatistics hub ↗04Final-year research
The project from question to defence
I’ll document the full journey here: proposal decisions, methods, analysis, findings, presentation and final report.
Planned for fourth yearOpen the project framework ↗01
Research questions & study designStudy design · Literature · Methods
↗02Statistical & biostatistical analysisData · Descriptive · Inference
↗03Field research & data qualitySurvey design · Digital collection · Data quality
↗04Scientific communication & presentationsVisuals · Reports · Presentations
↗ALLSee the case studiesInspectable methods, decisions and limitations
→Start with the data risk
Choose the next step
your evidence can support.
Use the practical guides to diagnose the problem, inspect the transparent case study, or move directly into a scoped NGO data-operations service.
GUIDE 01
NGO data quality audit checklist
Review indicators, completeness, logic, field signals, governance and deliverables before donor reporting.
Read the checklist →GUIDE 02KoboToolbox & ODK data quality monitoring
Build a safe live workflow from form controls and sync to human review, cleaning logs and approved exports.
Open the workflow →GUIDE 03Prepare survey data for analysis
Preserve raw records, document cleaning decisions and pass an analysis-readiness gate before modelling.
Prepare the dataset →SYNTHETIC CASE STUDYSee the audit trail, not a vague promise.
122 demonstration records, documented QA findings, GPS scope, a withheld test and a corrective-action plan—with evidence limits left visible.
Inspect the case study →About Research Metrics Africa
Evidence that works in the real world.
Research Metrics Africa is a Kenyan research and data practice led by Lawrence Okoth Muga. We combine biostatistics training, field-research experience, digital data work and practical communication to help clients turn complex questions into useful evidence.
Current focusResearch · Biostatistics · Evidence
Working toolsPython · R · SQL · SPSS · Excel
ExperienceSurveys · Fieldwork · Digital records
Based inKenya · Working worldwide online
Let’s talk
What question are you working on?
Tell us your objective, what data or evidence you have, your timeline and the outcome you need. We will tell you honestly whether we can help.