Biomedical Statistical Analysis
Reproducible statistical analysis for clinical studies, cohorts and registries, including longitudinal models, survival, missing data and scientific reporting.
Predictive Models & Patient Stratification
We develop and evaluate models for risk, prognosis and response patterns. Exploratory subgroup discovery, individual prediction and evidence of treatment-effect differences are kept distinct.
What is included
- Define the prediction objective, population, horizon and predictors available at prediction time.
- Use regression, classification, clustering and responder profiling as supported by the question and sample.
- Apply appropriate cross-validation or data separation, discrimination, calibration and stability analysis.
What you receive
- Specification, code and feature/model pipeline.
- Performance and validation report with uncertainty.
- Interpretable profiles and recommendations for further validation.
Frequently asked questions
Does finding responders establish differential benefit?
Not necessarily. A response-associated profile may reflect prognosis or selection; effect modification requires an appropriate comparison and analysis.
Related services
Longitudinal, Survival & Sensitivity Analysis
Repeated-measures, mixed-effects and time-to-event analysis for clinical studies: covariates, censoring, missingness and sensitivity.
RWE & Intervention Effect Analysis
Observational, post-marketing, pragmatic and before-after study analysis: adherence, outcomes, covariate adjustment and sensitivity.
Discuss your project
Describe the objective, study stage and deadline. We will confirm fit, deliverables, timing and a quote based on complexity and data quality.
Do not email patient, clinical or confidential study data. Access and the working environment are agreed before materials are shared.
Discuss your project