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[BSc], GPH

Admission Requirements

Quantitative Research Methods


Use of formal statistical procedures in the evaluation of evidence for biomedical research or in decision making is becoming ever more important. Methods such as logistic regression, Cox regression or Kaplan-Meier survival estimation for example, are ubiquitous in the scientific medical literature. A complete understanding of results presented will often require basic proficiency in the methods used. Evidence-based approaches to medicine or management of public health services frequently involve statistical approaches.

The purpose of this course is to acquaint you with some of the main statistical methods and concepts used in either research or management for medical practice and public health. We will focus on concepts and the reasons for the methods proposed. Methods will be illustrated and introduced from practical motivating examples. Emphasis will be on the motivation for the methods discussed and the interpretation of summary statistics that may be derived from them. Applicability of methodology for specific practical applications will be reviewed. We will also critically evaluate suitability of methodology for specific study designs and identify possible misuses or incorrect interpretations of statistical measures. You will learn to apply these methods for the analysis of real data in biomedical studies examples using statistical software. You will learn to identify appropriate methodology for specific practical applications and formulate conclusions based on evaluation of results generated from practical data analysis using the methods discussed in the course.

In addition to the above learning objectives, the course will introduce and discuss important example applications, such as in clinical trials research, family-based studies or quality control for public health service assessment, among others.



  • Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health) (Springer) 2012 Vittinghoff, Glidden, Shiboski and McCulloch

All other reading materials are only suggestions in case you need more support, or if you are interested.

The following are optional additional reading materials for people with an interest in medical statistics

  • Essentials of Medical Statistics, by Betty Kirkwood

  • Regression Models as a Tool in Medical Research, by Werner Vach

  • Statistical methods in cancer research. Volume 1 – The analysis of case-control studies. WHO. International agency for research on cancer. 1980.

  • Statistical methods in cancer research. Volume 2 – The design and analysis of cohort studies. WHO. International agency for research on cancer. 1987.

Literature on clinical trials:

  • Clinical trials. A practical approach. Stuart J. Pocock.

  • Statistical issues in drug development. Stephen Senn

There is a large body of literature on introductory medical statistics. This is a (non-exhaustive) list which you could consult if you want more support:

  • Introductory Applied Biostatistics (with CD-ROM) , by Ralph D’Agostino

  • Understanding Biostatistics, by Anders Källén

  • Medical Biostatistics, Third Edition (Chapman & Hall/CRC Biostatistics Series), by Abhaya Indrayan

  • Biostatistics: A Methodology For the Health Sciences, by Gerald van Belle

  • Biostatistics with R: An Introduction to Statistics Through Biological Data (Use R!), by Babak Shahbaba

  • Biostatistics: A Foundation for Analysis in the Health Sciences, by Wayne W. Daniel