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Discipline I · INSECAB Analytical Framework

Clinical biostatistics

Training in the design and statistical analysis of clinical studies. This is not about applying formulas: it is about learning to choose the analytical strategy that fits each research question and to document it rigorously.

Why do so many clinical manuscripts run into trouble in peer review?

One frequent error is not technical but strategic: defining the analysis method after the data have been collected, instead of planning it from the study design onwards. Clinical Biostatistics at INSECAB begins with the design, not with the spreadsheet.

Every analysis is documented reproducibly, with open, audited code, so that any co-author or reviewer can verify each methodological decision. That is what helps a manuscript arrive better prepared for the review process.

Principles of the INSECAB approach

Design first, analysis second

The statistical strategy is defined before any data are collected, not as a patch afterwards.

Reproducibility as the standard

Every analytical pipeline is documented in verifiable open code.

Clinical interpretation, not just p-values

Results are translated into the language of the real clinical decision.

Aligned with international guidelines

STROBE, CONSORT, TRIPOD and PRISMA built in from the start.

Areas of application


01

Clinical study design

Observational studies, clinical trials and prospective cohorts. Defining the sample size, the outcome variables and the analytical strategy before a single data point is collected.

02

Advanced regression models

Logistic, linear and Poisson regression and mixed models. Internal validation with bootstrapping and cross-validation. Calibration and clinical interpretation of the results.

03

Survival analysis

Kaplan–Meier, Cox models with the proportional hazards assumption, competing risks and time-dependent covariates. Reporting in line with international guidelines.

04

Predictive modelling and Decision Curve Analysis

Building and validating clinical risk scores. Assessment of net benefit with DCA to determine whether a model adds real value to decision-making.

05

Reproducible reporting for publication

Reports generated with Quarto/R Markdown, aligned with STROBE, CONSORT and TRIPOD. Full documentation of the analytical pipeline to facilitate peer review.

Who it is for

Professionals who want to strengthen their analytical capability.

—Physicians taking part in or leading clinical studies
—Researchers preparing publications in first-quartile (Q1) journals
—Residents and research fellows working on their doctoral thesis
—Hospital teams with accumulated data still awaiting analysis

In the INSECAB programme you will learn

  • ✓ R for reproducible clinical analysis
  • ✓ Regression, survival analysis and mixed models
  • ✓ Validation and interpretation of predictive models
  • ✓ Reporting with Quarto for publication
  • ✓ Preparing responses to reviewers with methodological argument