JH Stat Statistical Consulting

JH Stat

Expert Statistical Consulting for Health Research

Independent statistical support for study design, grant applications, advanced analysis, psychometrics, publications and research training.

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Jamal Hossain, PhD, Founder and Principal Statistician at JH Stat

Jamal Hossain, PhD

Founder and Principal Statistician

About JH Stat

Rigorous statistical thinking, from first idea to final publication

JH Stat is an independent statistical consultancy founded by Jamal Hossain, a UK-based applied health statistician, researcher and university academic with more than ten years of experience in statistics, research methods and quantitative analysis.

The consultancy provides statistical consultancy, research collaboration and training to universities, healthcare organisations, research teams, charities, health technology organisations and doctoral researchers. Work ranges from a short methodological review of a draft protocol through to sustained analytical collaboration across the life of a funded study.

The emphasis throughout is on methods that are appropriate to the question, defensible under peer review, clearly explained to non-statisticians, and reproducible by others.

Read more about JH Stat and Jamal Hossain

How engagements usually begin

  1. Initial enquiry. A short description of your study, timescale and the support you need.
  2. Scoping conversation. An initial scoping conversation can be arranged, to establish whether the work is a good fit.
  3. Written proposal. The scope, timescale and fees are agreed in writing before any chargeable work begins.
  4. Delivery. Agreed outputs, documented code where relevant, and time set aside to talk the results through.

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Services

How JH Stat can help

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.

Study Design and Protocol Development

Sharpening research questions, choosing designs and outcomes, and writing statistical analysis plans that stand up to scrutiny.

Sample Size and Power

Justifiable sample size and power calculations, including clustered, longitudinal and pilot designs, with sensitivity assessments.

Statistical Analysis

Regression, multilevel and mixed-effects models, longitudinal and survival analysis, causal methods and machine learning where appropriate.

Psychometrics and Measurement

Factor analysis, reliability, construct validity, and the development and validation of scales and patient-reported outcome measures.

Grant and Funding Support

Statistical methods sections, analysis plans, sample size justification and reviewer responses, developed collaboratively with your team.

Publications and Statistical Review

Independent statistical review of manuscripts, interpretation of results, reporting guidance and reproducibility checks before submission.

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Areas of expertise

Methodological and applied strengths

Applied research areas

  • Applied health statistics
  • Clinical and observational research
  • Health services research
  • Public health and population health research
  • Patient-reported outcomes and measurement

Statistical methods

  • Multilevel, mixed-effects and longitudinal models
  • Survival and time-to-event analysis
  • Psychometrics, factor analysis and scale validation
  • Causal inference, including propensity scores, interrupted time series and difference-in-differences
  • Machine learning and predictive modelling in health research

Explore research interests in more depth

Who JH Stat supports

Working with research teams across the health sector

Clients and collaborators typically come from research-intensive settings where statistical quality has direct consequences for funding, publication and practice.

  • Universities and academic research teams
  • NHS and healthcare researchers
  • Clinical and health research organisations
  • Charities and public-sector research teams
  • Health technology companies
  • Doctoral researchers seeking methodological support
  • Organisations commissioning statistical training

Why work with JH Stat

Academic rigour with the responsiveness of an independent consultant

Health research specialism

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.

Active academic practice

Consultancy sits alongside ongoing university teaching, supervision and research, which keeps methods current and grounded in day-to-day research practice.

Clear communication

Results are explained in language that clinicians, funders and non-specialist collaborators can act on, without diluting the underlying statistics.

Reproducible by design

Analyses are scripted, version-aware and documented, so that findings can be re-run, audited and extended after the engagement ends.

Honest about uncertainty

Limitations, assumptions and sensitivity analyses are reported openly. Where the data cannot answer the question, that is said plainly.

Flexible engagement

Support can be a single review, a defined package of analysis, a named collaborator on a grant, or recurring advisory time for a research group.

Selected experience

Background

A summary of professional and academic experience. Fuller detail is available on the about page and in the CV.

  • Current

    Senior Lecturer in Applied Health Statistics

    Teaching, supervision and research in applied health statistics, including statistical training for postgraduate and professional audiences.

  • Current

    Founder and Principal Statistician, JH Stat

    Independent statistical consultancy, research collaboration and training for health research organisations and individual researchers.

  • Ongoing

    Research collaboration on externally funded projects

    Statistical contribution to multidisciplinary health research, including design, analysis and reporting on externally funded studies.

  • Doctoral

    PhD in Social Statistics and Demography

    Quantitative research training in advanced statistical modelling of complex, hierarchical and longitudinal population data.

Software and tools

Analysis is delivered in whichever environment suits your team, with code and outputs shared in a form your collaborators can use.

  • R — modelling, reproducible reporting, package-based workflows
  • Stata — applied health and epidemiological analysis
  • SPSS — analysis and teaching for applied research teams
  • AMOS — structural equation and path modelling

Git, Quarto and R Markdown are used alongside these to support version control and reproducible reporting.

Publications

Selected publications

Peer-reviewed research spanning applied health statistics, measurement and quantitative methods.

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Training

Statistical training and workshops

Practical, applied training for research teams, delivered online or in person and tailored to the data your group actually works with.

See training options Enquire about a workshop

Popular topics

  • Introduction to R for health researchers
  • Applied regression modelling
  • Multilevel and mixed-effects modelling
  • Survival analysis in practice
  • Sample size and study design
  • Reproducible analysis and reporting
  • Analysis in SPSS and Stata for applied teams

Discuss your project

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.

Start an enquiry Email [email protected]