The Master’s Degree in Advanced biostatistics for medical research, promoted by the Unit of Biostatistics, Epidemiology, Public Healthcare of the Department of Cardiac-Thoracic-Vascular Studies and Public Healthcare of the University of Padua, prepares professional statistic figures with high skills of identifying, drawing and analysing medical studies.

The Master’s Degree is aimed at exploring advanced topics in statistics for medical research. These topics are relevant for the pharmaceutical industry and CRO (Contract Research Organizations). The Master’s is addressed to internal personnel who can update professionally, or new levers that aim at specializing in this new sector.

It is a second level short specialisation course in on-line and on-demand mode.

The training activities of the Master’s Degree in Advanced biostatistics for medical research is organized in five modules, covering topics such as:

  • Cost analysis in medical trials and in observational studies;
  • Bayesian drawings for pharmacological testing and devices;
  • Meta-analysis networks;
  • Missing data and estimations;
  • Propensity scores for non-randomized clinical trials.

The training project is aimed at exploring advanced topics in statistics for medical research.

The Master’s Degree in Advanced biostatistics for medical research provides technical and scientific training for professional statistics figures with high skills in identifying, designing and analysing clinical studies with innovative, non-standard methods. Moreover, one of the specific figures is that of the biostatistician who works or wants to work in the public or private pharmacological research field.

The topics covered are relevant for the pharmaceutical industry and CRO (Contract Research Organizations), which need to develop internal competencies or acquire personnel trained on them. The Master’s Degree bridges this gap, by promoting a statistical preparation closer to the needs of companies and to new emerging methodologies.

The Master’s Degree in Advanced biostatistics for medical research provides training on:


Preserving the analysis’ initial randomization is important to prevent preconceptions and provide a solid base for statistical testing.


Experimental Bayesian drawings can incorporate historical data or information from published literature, thus saving time and costs and minimizing the number of subjects exposed to lesser treatment. Moreover, they can adapt to unexpected protocol changes and allow researchers to explore the plausibility of the different results, before patients are enrolled in the study.


Where there is the need to compare three or more treatments for the same clinical indication, meta-analysis networks offer the important advantage of summarizing all the evidence available in a single analysis, thus allowing to better construe these multiple comparison situations, which have become very frequent in the last years.


  • Introduction to the causal effect: definition of the outcome variable, causal variable (or treatment) and potential confounding factors; definition of potential resulting concepts; definition of average relevant quantities (ATE, ATT, ATC).
  • Definition of causal interference in experimental research, with particular focus on valid causal inference hypotheses (casual unit selection, casual treatment allocation, and large samples).
  • Definition of the propensity score and its role in the causal inference process, within observational studies.
  • Identification and definition of the most widespread propensity score methods: matching, layering, covariates adjustment and reverse probability pondering.
  • Strategies for a solid analysis implementation with propensity matching, the most used method: potential confounders selection, propensity score estimate, choice of matching algorithms, common support check, quality analysis and sensibility match check.
  • Comparison of the propensity score with other methods.


Linear mixed models are appropriate statistical techniques to analyse clustered data and model the correlation between units of the same cluster. The objectives of the module are providing a general theoretical framework of linear mixed models and showing how to use them in practice, by describing the potential benefits they can provide, compared to more traditional statistical techniques.


The second level Master’s Degree in Advanced biostatistics for medical research is issued online, so that it can be followed also by full-time workers; it is issued on demand through UniPD multimedia Moodle platform, and video-lessons are available 24/7. It has been designed for students and professionals who want to combine other professions and activities with the need to qualify or further specialize.

Lessons will start in November 2022, and the course will last one year.

There will be a frequent and easy interaction between students and professors, through Moodle’s Forum.

The Master is divided into several 4-week modules, between November and May. At the end of each module, attendees will have the time to rewatch the video-lessons, followed by on-demand homework to test the competencies acquired. The project work to discuss the final exam will be drafted between June and July, and it may include cases that specifically interest the student, as agreed with the tutor. The work – prepared during the summer – will be the basis for the diploma-awarding discussion in September, on the Zoom platform.

For more information on the Directors and Professors, and for useful insights on the Master’s Degree in Advanced biostatistics for medical research, here’s the presentation video:  Advanced Biostatistics for Medical Research | Department of Cardiothoracic-Vascular Sciences and Public Healthcare | University of Padua (


Health, environment and territory
€ 2.022,50
€ 1.000,00
Find the admission titles in the selection notice 22/23


There will be no stages/traineeship, as they are deemed to be irreconcilable with the profile of the Master’s attendees. However, students will have the chance to tackle actual scientific matters and databases, proposed by the Direction during the lessons and the project works. There will be a final project work that can be completed also on the student’s workplace analysis and data. The topic will be agreed with the course’s professors.

No, there will be no an admission test. However, being a Level 2 Master’s Course, it can be accessed by anyone who holds a master’s degree or specialist degree in one of the fields specified in the reference call. Evaluation is based on the titles, within the fields specified on the official call.

Unfortunately, there won’t be any form of facilitation. Pursuant to Art. 2 of the Regulation for University Master’s Degree, Postgraduate Course and Higher Education Courses, there is the option of supernumerary admission for University staff with a permanent contract, to the extent of 10% of the maximum quantity of applicants that can be enrolled in each Master’s Course. The enrolment quota for the University administrative-technical staff (PTA) is equal to 20% of the quota provided for each Master’s Course.

Attendance is mandatory, even if the course is held online. A maximum absence threshold of 30% is allowed. However, since video-lessons are pre-recorded, they can be watched at any time, and it is therefore easy to catch up with the study plan. The course administrative office and the professors are available to help students in case of onerous engagements of periods of intense work.