2007-2008 Session
October 10th 2007, 2pm to 5pm at MANDEC (Manchester Dental Education Centre), Higher Cambridge Street (tea will be served about mid-afternoon) (building 41, entrance on corner facing building 35) Joint meeting with
Manchester University's Biostats Group Theme: "Developments in Longitudinal Data Analysis" GEERT MOLENBERGHS (University of Hasselt, Belgium)Unified approaches for surrogate marker evaluation from multiple randomized trials The validation of surrogate endpoints has been initially studied by Prentice and Freedman. Noting operational difficulties, Buyse and Molenberghs proposed instead to use jointly the within-treatment partial association of true and on the true outcome. In a multi-centre setting, these quantities can be generalised to individual-level and trial-level measures of surrogacy. Buyse and colleagues have proposed a meta-analytic framework to study surrogacy at the trial and individual-patient levels. Variations for various endpoints have been developed. Efforts have been made to converge to a common framework. This includes a so-called variance reduction factor and an information-theoretic approach. Work has been done regarding sample size assessment, leading to the surrogate threshold effect. JIANXIN PAN (Univeristy of Manchester)
In tumour xenograft experiments, several treatment regimens are administered and tumour volume for each individual is measured repeatedly over time. When modelling such data, certain constraints are imposed on regression parameters to account for intrinsic growth of tumour in the absence of treatment. On the other hand, survival data and cure data are observed due to a portion of individuals who may be curved and so never experience the event. In this talk, we will show how to jointly model the longitudinal, survival and cure data in order to account for the possible association of those data. Simulation studies show that the proposed joint modelling approach does improve the separate modelling in terms of mean square errors of parameter estimates. Joint modelling for longitudinal, survival and cure data in tumour xenograft experimentsFRANK WINDMEIJER (University of Bristol)
A commonly used estimation procedure to estimate the parameters in dynamic panel data models with constant unobserved individual specific heterogeneity is to transform the model in first differences and use observations on the variables in the past periods to instrument the endogenous differenced explanatory variables, and estimate the parameters by GMM. Weak instrument problems arise when the series are very persistent. The presentation will show the effects of this weak instrument problem on the estimation results, discusses tests for the detection of weak instruments and the relative merits of using different moment conditions and/or different estimation techniques, given the moment conditions. 12 December, 5pm, Room E32, John Dalton Building, Manchester Metropolitan University, Oxford Road (opposite BBC). Regulations often require structures such as sea defences, reservoir walls, oil rigs and tall buildings to be strong enough to withstand the worst conditions likely to be encountered during a specified period, usually longer than that over which observations have been made. Statistical methods give a rational approach to such extrapolation problems, not claiming clairvoyance but indicating the best use of past data and attempting to estimate the uncertainties in predictions. The talk will describe some environmental and engineering applications of extremal statistical theory. Meeting contact: Stephan Rudolfer February 13th 2008, 5pm, Room E32, John Dalton Building, Manchester Metropolitan University, Oxford Road (opposite BBC). In 2005 Lancaster University was awarded a multi-million pound grant to fund a Centre of Excellence in Teaching and Learning (CETL). The Lancaster Postgraduate Statistics Centre (PSC) has the core aim of promoting excellence in teaching statistics to postgraduates across a range of disciplines. The diverse interests of the Statistics group provide a unique research-led approach to teaching with a strong practical emphasis on skills acquisition. This talk will describe the breadth and diversity of the work of the new centre. March 12th 2008, 5pm, Room E32, John Dalton Building, Manchester Metropolitan University, Oxford Road (opposite BBC). Compositional data sets occur in many disciplines and give rise to some interesting statistical considerations. In recent years, the modelling and forecasting of compositional time series has seen some important developments, although this approach does not seem to be widely known. This talk represents a modest step towards rectifying this. After briefly setting out the basic structure of compositional data sets and outlining the implications for forecasting compositional time series, it illustrates the techniques using three examples: modelling and forecasting expenditure shares in the U.K. economy; forecasting trends in obesity in England; and examining shifts in the proportions of English first class cricketers born during particular quarters of the year. May 14th 2008, 5pm, Room E32, John Dalton Building, Manchester Metropolitan University, Oxford Road (opposite BBC).
In the simplest cases of disputed paternity we will have evidence in the form of DNA profiles from the child, mother and putative father: it is then relatively straightforward to determine the strength of the evidence bearing on paternity. But often the putative father is unavailable for testing, and instead we have to make do with DNA from one or more of his relatives. Other features, such as mutation, silent alleles, laboratory and handling errors, etc., introduce additional complications. The task of interpreting the forensic evidence in such cases can become extremely challenging, both logically and computationally. Recently it has been shown how the technology of Bayesian networks -- especially in its "object-oriented" version -- can be used to represent and solve such problems. I will describe the basics of this approach, present a collection of fundamental networks that can be flexibly combined (like a child's construction kit) to represent a very wide range of problems arising in forensic genetics, and illustrate their use in some real cases. July 9th 2008, 4.30pm, Mordell Room (G.209), Alan Turing Building, University of Manchester
Note the change in venue
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