Study design and protocol development
Sharpening research questions, choosing designs and outcomes, and writing statistical analysis plans that stand up to scrutiny.
JH Stat
Study design, sample size, statistical analysis, psychometrics, grant support and research training for university, NHS, charity and health technology research teams.
Jamal Hossain, PhD
Founder and Principal Statistician
Services
Support at any stage of the research cycle, scaled to the size of the question — from a single sample size calculation to full analytical collaboration on a funded programme.
Sharpening research questions, choosing designs and outcomes, and writing statistical analysis plans that stand up to scrutiny.
Justifiable sample size and power calculations, including clustered, longitudinal and pilot designs, with sensitivity assessments.
Regression, multilevel and mixed-effects models, longitudinal and survival analysis, causal methods and machine learning where appropriate.
Factor analysis, reliability, construct validity, and the development and validation of scales and patient-reported outcome measures.
Statistical methods sections, analysis plans, sample size justification and reviewer responses, developed collaboratively with your team.
Independent statistical review of manuscripts, interpretation of results, reporting guidance and reproducibility checks before submission.
Areas of expertise
JH Stat provides medical statistics and biostatistical support for health, clinical and health services research, from study design and measurement through to analysis and reporting.
Why work with JH Stat
The work is concentrated in health, clinical and health services research, so methods are matched to the realities of those data and the expectations of those journals and funders.
Results are explained in language that clinicians, funders and non-specialist collaborators can act on, without diluting the underlying statistics.
Analyses are scripted, version-aware and documented, so that findings can be re-run, audited and extended after the engagement ends.
Limitations, assumptions and sensitivity analyses are reported openly. Where the data cannot answer the question, that is said plainly.
Software
Analysis is delivered in whichever environment suits your team, with code and outputs shared in a form your collaborators can use.
Git, Quarto and R Markdown are used alongside these to support version control and reproducible reporting.
Publications
Peer-reviewed research spanning applied health statistics, measurement and quantitative methods.
2026 Article
2026 Article
2025 Article
Training
Practical, applied statistical training for research teams, delivered by a practising statistician — online or in person, and tailored to the data your group actually works with.
Whether you need a sample size justification for a single study or a statistical collaborator for a multi-year programme, an initial scoping conversation can be arranged. The scope, timescale and fees are agreed in writing before any chargeable work begins.