IBS Italy

International Biometric Society - Italian region



Also this year the IBS Italian region promotes the Statisticalps course. In this post you can find the first available details.


*– STATISTICALPS: course on medical statistics in the Alps –*


We are pleased to announce that the 9th edition of the STATISTICALPS residential course will be a “Winter edition” – 2nd-5rd March 2020, Ponte di Legno (Brescia, Italy).

* — Instructors –*

Richard Cook, Professor of Statistics in the Department of Statistics and Actuarial Science at the University of Waterloo in Canada http://www.math.uwaterloo.ca/~rjcook/

Daniel Farewell, Reader of Statistics in the School of Medicine at the Cardiff University in UK https://www.cardiff.ac.uk/people/view/123049-farewell-daniel



This course will provide an introduction to statistical methods for the analysis of longitudinal and life history data. An emphasis will be given to the kinds of data arising in epidemiology and public health research, with some issues being specific to the analysis of data from clinical studies.

The course will begin with a focus on common approaches for the analysis of repeated measurements from individuals over common scheduled assessment times, including mixed effects models, generalized estimating equations, and autoregressive models. Models and methods will then be discussed for the analysis of life history data obtained from continuous observation of individuals who are subject to right-censoring.

Following an introduction to survival analysis, methods or the analysis of recurrent event and multistate data will be covered. When data are only available from individuals at intermittent clinic visits, the underlying processes of interest are incompletely observed. Strategies for dealing with such data will be discussed for longitudinal marker processes, failure time processes and multistate models.

The assumptions justifying the various approaches to analysis will be highlighted, and the interpretation of covariate effects and other possible estimands will be emphasized. Recurring themes will include robustness, the implications of a dependence between the longitudinal or life history process and the observation process (i.e. missing data, censoring and informative observation mechanisms), and causal inference. Substantive examples from medical science will be used throughout the course to motivate the methods and illustrate the different interpretations given to estimates of intervention and other covariate effects. R code and selected output will be provided in worked examples.


A detailed program with fees and deadlines can be found in the brochure:

You can email us at statisticalps@unimib.it 

You can also follow us on

Facebook https://www.facebook.com/Statisticalps-Course-on-Medical-Statistics-9th-edition-2243932959157446/

Twitter @StatisticAlps

PhD position in Public Health Sciences at University of Milan, Italy.

The PhD in Public Health Sciences is mostly directed to young candidates whose interest is to develop research on international topics including clinical and epidemiological settings. To facilitate a multidisciplinary approach, the PhD in Public Health Sciences is open to young graduates belonging not only in the medical and health-care fields but also in other scientific fields, such as Biology, Biotechnology, Veterinary medicine, Statistics, Sociology, and Economics.

Successful candidates will receive a fellowship by the University of Milan, and will work in an interdisciplinary and stimulating environment.

The fellowships are for a period of 3 years, starting from October 2019.

The interested candidates must apply to the Ph.D call that is currently open online at the website




The deadline for applications will be 24 june 2019 (14:00)

For further information please contact:

Prof. Carlo La Vecchia – carlo.lavecchia@unimi.it

Chiara Padovese – chiara.padovese@unimi.it

Women’s day in Mathematics, May 10th 2019

We at SIB have welcomed the invitation of many international scientific societies to celebrate women’s day in mathematics, identified with May 12 (https://may12.womeninmaths.org/).
In particular, SIB organized on May 10th, an event that focuses not only on the contribution of women in biostatistics research but also on biostatistics in research for women’s health. You’re all invited.

The flyer with all the details can be downloaded here:

Italian Bayesian Day for Clinical Research, Torino, May 10th 2019

Il 10 maggio a Torino presso la sala Principi D’Acaja del rettorato dell’università di Torino, l’Italian Biostatistics Group (IBIG), una società di statistici farmaceutici italiani e membro italiano della EFSPI (https://www.efspi.org/), organizza la prima edizione dell’”Italian Bayesian Day for Clinical Research”. Si dibatterà di aspetti classici e innovativi della metodologia bayesiana applicata allo sviluppo clinico. Relatori provenienti dall’accademia e dall’industria proporranno diverse prospettive sull’impiego della statistica bayesiana, ancora poco utilizzata nel contesto della ricerca clinica.

Particolare attenzione sarà rivolta al ruolo della statistica bayesiana nei processi decisionali, dalla determinazione della dimensione campionaria, all’analisi dei dati, alla pianificazione degli studi clinici. L’evento sarà tenuto in lingua inglese.

Per ulteriori informazioni e modalità di registrazione: https://simef.it/index.php?option=com_eventbooking&view=event&id=478&catid=7&Itemid=386&lang=it

Ci sono limitate possibilità di finanziamento per la partecipazione di studenti.

Research fellowship @ CUSSB – Milano

Sarà emesso a breve (entro fine giugno) un bando per un assegno di ricerca nel settore statistico per un periodo di un anno – rinnovabile – per un’attività di ricerca da svolgersi presso il CUSSB (Unisr-Milano).
L’obiettivo della ricerca è quello di sviluppare tecniche di data-integration per la modellizzazione di dati di diversa natura, elettrofisiologici, neurofisiologici, scale psicometriche, nella valutazione delle emozioni. In particolare, si andrà a studiare la struttura di dipendenza tra risposta soggettiva, risposta oggettiva psicofisiologica e le misure di efficacia associate a messaggi visivi (da media/social media) a forte valenza emotiva per valutarne l’ impatto informativo.
Il contesto di applicazione va dalla valutazione delle campagne in Sanità al social marketing piu’ in generale. Il progetto coinvolgerà candidati particolarmente motivati a lavorare in un contesto multidisciplinare (statistica, biomedicina, psicologia, bioingegneria).

Il bando è indirizzato a giovani in possesso di un dottorato di ricerca (in materie statistico-quantitative) con competenze nell’ambito di network possibilmente anche in contesti tempo-varianti. In attesa dell’emissione del Bando Ufficiale invito tutti gli interessati ad inviare il loro curriculum già da ora alla mia attenzione (diserio.clelia@hsr.it).

Network inference in biology and disease, 10 – 13 September 2019, Naples, Italy

Network inference for modeling complex systems is becoming a central theme in biology and disease. However, network inference is a fast evolving aspect of data science in biological and biomedical research. The objective of this EMBO Workshop is to bring together experts from different disciplines to present and discuss their latest findings in using network inference and network integration for modeling the complexity of biological systems at the molecular dynamic and genetic levels. The workshop will facilitate trans-disciplinary interactions around new approaches and current biological and biomedical questions and showcase frontier research in network inference and biology.

More information can be found here:


Postdoc, Department of Biostatistics at Columbia University

Dr. Linda Valeri in the Department of Biostatistics at Columbia University Mailman School of Public Health is seeking a Postdoctoral Research Fellow. The position is available immediately. The one-year position can be extended to additionally two years on the basis of performance, evaluated at the end of each year. This position will provide the opportunity to carry out causal inference research in either or both of two collaborative avenues:

  • The investigation of environmental mixtures health effects in the context of Bangladeshi and American perinatal and adult intergenerational cohorts in collaboration with the Department of Environmental Health Sciences at Columbia University and Harvard University.
  • The analysis of mobile passive (GPS, call/text logs, sleep data) and active (surveys) data streams in collaboration with the New York Psychiatric Institute, NY, the Departments of Psychiatry at Columbia University and Harvard University, and McLean Hospital.

The broad goal of the successful candidate will be the development and application of blended causal inference and machine learning approaches and automated software tools. The approaches will be applied to harness exposomic data and mobile health data to investigate the joint causal effects of environmental and behavioral factors over time to inform policy on environmental mixtures and to discover behavioral targets of treatment in psychosis. The postdoctoral fellow will have the opportunity to collaborate with scientists across fields and across domestic and international research institutions.

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