ABS08 - 2008 Applied Bayesian Statistics School
BAYESIAN DECISION PROBLEMS IN BIOSTATISTICS AND CLINICAL TRIALS
Centro Congressi Panorama, Trento, Italy
9 - 13 June, 2008
Francesca Ieva, Politecnico di Milano, Italy
The Milano network for acute coronary syndromes and emergency
services: a biostatistical case study
An important open problem in the study on in-hospital
mortality and successfulness of reperfusion therapy for patients with
ST-Elevation Myocardial Infarction (STEMI) is to point out the most significant
prognostic factors which influence these outcomes. On the basis of a wide set of
data collected in the urban area of Milano (in 2006-2008), the subject of my
master thesis is the study of suitable statistical techniques to analyze these
data (exact confidence interval for Odds Ratio, nonparametric estimation of
Odds Ratio dependent on continuous covariates, nonlinear regression models,
etc.) in order to gain useful results which could help and support medical
analyses and strategic decisions.
Valeria Vitelli, Politecnico di Milano, Italy
k-means clustering and principal points: an open problem on
functional data
The field of statistics has recently been strongly challenged, mainly in the
biostatistics area, by the problem of performing new techniques to deal with
functional data (growth curves, cardiovascular geometry, etc.); one of the most
important aims of these techniques is to detect and classify different patterns,
and eventually to elicit a representative element for each group. The open
problem, subject of my master thesis, is to find in this functional framework
the links between classical clustering algorithms (k-means, etc.) and the theory
of principal points, already proved in the multivariate setting.
Tobia Sing, Novartis, Switzerland
Visualizing classifier performance in R using ROCR
ROCR is a package for evaluating and visualizing the performance of
scoring classifiers in the statistical language R. It features over 25
performance measures that can be freely combined to create two-dimensional
performance curves. Standard methods for investigating trade-offs between
specific performance measures are available within a uniform framework,
including receiver operating characteristic (ROC) graphs, precision/recall
plots, lift charts and cost curves. ROCR integrates tightly with R's
powerful graphics capabilities, thus allowing for highly adjustable plots.
Being equipped with only three commands and reasonable default values for
optional parameters, ROCR combines flexibility with ease of usage.
AVAILABILITY: http://rocr.bioinf.mpi-sb.mpg.de. ROCR can be used under the
terms of the GNU General Public License. Running within R, it is
platform-independent.