TANITY Global Med CommsAnalyse data with transparent reasoning
We support data cleaning, model selection, and interpretation with clear reporting of assumptions and limitations.
Who this service is for
- Students preparing quantitative results chapters
- Clinicians needing biostatistical guidance
- Researchers interpreting observational or experimental data
- Teams requiring reproducible analysis workflows
What we assist with
- Data cleaning plans and code review
- Model selection with assumptions and diagnostics
- Effect size, confidence interval, and p-value interpretation
- Tables, figures, and reporting aligned to journal standards
- Reproducibility checklists and analysis narratives
How the process works
Initial consultation
Review dataset structure, research questions, and planned analyses.
Scope alignment
Agree on analytic approaches, software, and outputs needed.
Expert input & feedback
Provide annotated guidance, diagnostics, and interpretation notes.
Final review & next-step guidance
Deliver reporting templates and replication-ready steps.
Quality, ethics & confidentiality
We respect data privacy, avoid overclaiming significance, and document limitations transparently. Sensitive data stay within your controlled environment.
Frequently asked questions
We can review code or co-run analyses with you; we emphasise understanding over black-box outputs.
We support R, Stata, SPSS, and Python, focusing on reproducible scripts.
Yes, we document and visualise diagnostics and discuss alternative models.
No, data ownership remains with you. We work on copies you provide securely.
We provide structured notes and edits; authorship stays with you.