Also this year the IBS Italian region promotes the Statisticalps course. In this post you can find the first available details.
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*– STATISTICALPS: course on medical
statistics in the Alps –*
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We are pleased to announce that the 9th edition of the STATISTICALPS residential course will be a “Winter edition” – 6-11 September 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
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THE ANALYSIS OF LONGITUDINAL AND LIFE
HISTORY DATA
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.
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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