Summer term seminars 2011
Giorgos Minas (Warwick Statistics Department)
A two-stage hybrid procedure for detecting global
treatment effects in multivariate clinical trials: theory and
applications to fMRI studies
Tuesday 17 Mai
12:30 13:30
(Room A117)
In phase II clinical trials with multivariate outcomes,
investigators are often interested in ascertaining whether,
globally, i.e. across the local outcomes, a therapeutic
strategy is more efficacious than an established alternative.
Such a global statement is particularly essential in the field
of the rapidly expanding neuroimaging studies where the
multivariate responses have highly correlated components
and the available sample size is typically small. In this
context we develop a two-stage frequentist/Bayesian
procedure testing the global hypothesis of equivalence
between the compared treatments effects. The first stage is
exclusively dedicated to gathering information used to
select optimally the auxiliary variables of the test
undertaken using the second-stage responses. The objective
function here is the predictive power given the information
collected from clinicians, historical data and the first stage
study while the auxiliary variables are the weights of the
linear combination of the multivariate responses used to
construct the classical z- and t-statistics. We apply our
methods to fMRI studies, where we find that it outperforms
standard single-stage testing procedures such as Hotelling's
T2 test. Finally, we discuss developments of the proposed
framework towards adaptive design and analysis.
Richard Crossman (WMS)
Using Imprecise Probability in Classification Trees
Tuesday 24 Mai
13:00 14:00
(Room A011)
Classification tress can be of great use in medicine,
allowing us to create algorithms for use in diagnostic
practice. Unfortunately, many of the available classification
methods can demonstrate unjustified certainty, choosing
one category over alternatives that are almost as plausible.
By using imprecise probability we can both increase the
accuracy of classification trees in many cases, but we can
also create credal classification trees, which are capable of
returning a set of categories in situations for which the data
does not justify the return of a single category. We can thus
potentially eliminate a large number of possibilities,
without forcing ourselves to accept a single option.
Summer term seminars 2011
Peter Kimani (WMS)
Estimation following an adaptive seamless design
Tuesday 21 June
13:00 14:00
(Room A117)
Ives Ntambwe (WMS)
Sample size re-estimation in clinical trials with multiple
endpoints
Abstracts: