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 

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Updated: September 3, 2019 — 12:20 pm
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