Statistics Applied to Clinical Research
Objectives
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
Code
191004
Credits
6
Responsible teacher
Prof.ª Doutora Maria da Conceição Lopes Costa
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese or English
Prerequisites
Bibliography
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:
1. Critical analysis of one paper that contains statistical analysis of associations;
2. Planning and design a real or hypothetical clinical study;
3. Data analysis using regression (linear, logistic, Cox);
4. 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.