FromRawDatatoDefensibleResults

We had more than a thousand patient files in the psoriasis registry, and honestly I did not know where to start. They organised everything in R and, step by step, we started to see patterns we did not expect. I felt I had a real partner in the project, not just someone doing a service.

We were running a Phase II trial on empagliflozin in non-diabetic kidney patients, and the statistics were honestly beyond our own team. They handled the randomisation and the analysis plan from the beginning, and when the reviewers asked difficult questions, the answers were already there in the report. This saved us a lot of time.

This was my PhD on burnout among ICU nurses, and the viva was my biggest fear. They sat with me and explained every test and every p-value until I understood my own data. On the day of the defense I was calm, and the committee could see that I really knew my analysis.

A network meta-analysis is not easy to do correctly, and many groups make mistakes in it. Their team followed the PRISMA steps properly, and the figures were clear for the readers. The journal accepted the paper with only minor comments — for this kind of work, that is rare.

Our work was not medical at all — we were studying the climate around a national rail corridor: temperature, humidity and wind across different periods. They built the statistical analysis and the GIS maps together, and the results helped us in real operational and safety decisions. Very professional people.

The bioinformatics part was what worried me most — the sequencing data was big and not clean. They processed it, ran the full pipeline, and explained the results in a way I could actually put into my paper. And there were no long revisions after, which I appreciated.

Adaptive designs are complicated, and we needed a team that truly understands interim analysis and stopping rules. They prepared the statistical plan for our anti-fibrotic trial and stayed with us through every interim look. The safety monitoring board was comfortable with the methods, and for us that was the most important thing.

Our study looked at vitamin D levels across the year in Riyadh, with more than five thousand samples. The data came from different clinics and was not consistent, but they handled the cleaning and the seasonal analysis in SPSS without any complaint. The final tables were ready for the ministry report directly.

We were building a real-world evidence registry for biologic therapies in rheumatoid arthritis across the GCC. The number of variables was very large, and the centres were not using the same definitions. They standardised everything and gave us an analysis we could defend in front of the regulators.