Statistics Applied to Clinical Research


Students of this course should be able to:

1. Perform clinical study planning and design, identify the appropriate statistical analysis and calculate the appropriate sample size;

2. Conduct a systematic review;

3. Perform and interpret meta-analysis;

4. Estimate effect sizes and perform statistical tests suitable to evaluate the statistical significance of different types of effects;

5. Use prediction models;

6. Discuss and evaluate the suitability of different statistical methods;

7. Perform critical analysis and interpret results of statistical methodologies found in clinical scientific papers.

General characterization





Responsible teacher

Prof.ª Doutora Vera Mónica Almeida Afreixo


Weekly - Available soon

Total - Available soon

Teaching language

Portuguese or English




·         Borenstein, M., Hedges, L.V., Higgins, J.P.T., and Rothstein, H.R. (2009). Introduction to Meta-Analysis.

NJ: Wiley.

·         Chow, S.C., Shao, J., and Wang, H. (2003). Sample size calculations in clinical research. Boca Raton: Taylor & Francis.

·         Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates.

·         Cox, D.R. (1972). Regression Models and LifeTables. Journal of the Royal Statistical Society. Series B (Methodological), Vol. 34, No. 2. , pp. 187220.

·         Hosmer, D.W. and Lemeshow S. (2004). Applied Logistic Regression. NJ: John Wiley and Sons.

·         Kleinbaum, D.G. and Klein, M. (2005). Survival Analysis: a Selflearning text. Berlin: Springer.

·         Rosner, B. (2011). Fundamentals of Biostatistics. Boston: Brooks/Cole Cengage Learning.

Teaching method

Lectures and classes: The contents of the syllabus are presented in the lectures and concepts are illustrated through exercises and problem solving.

The course includes a TP in which several clinical studies and the corresponding statistical methods are exploited. Includes a critical discussion of the application of the syllabus in published papers. Support materials are available on (moodle).

Evaluation method

The evaluation of the course is performed using continuous assessment:

·         Critical analysis of one paper that contains statistical analysis of associations;

·         Planning and design a real or hypothetical clinical study;

·         Data analysis using regression (linear, logistic, Cox);

·         Reproduction / Preparation / Updating of a meta-analytical study.

Subject matter

1. Basic statistical concepts and exploratory data analysis;

2. Experimental designs and power analysis;

3. Systematic review and meta-analysis;

4. Predictive modelling and survival analysis.


Programs where the course is taught: