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Room 4192, 2207 Main Mall, Vancouver
Tue 29th July 2014
Professor, University of Padova, Italy
Combination based permutation tests: theory and applications
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In recent years permutation testing methods have increased both in number of applications and in solving complex multivariate problems. Permutation tests are essentially of an exact nonparametric nature in a conditional context where conditioning is on the pooled observed data set which is generally a set of sufficient statistics in the null hypothesis.

There are many complex multivariate problems which are difficult to solve outside the conditional framework and in particular outside the nonparametric combination (NPC) of dependent permutation tests method. We discuss this method along with some application in different experimental or observational situations (e.g. in biostatistics).Some recent properties and features of combination-based tests are also presented.
Room 4192, Earth Sciences Building, 2207 Main Mall, Vancouver
Thu 24th July 2014
Vivien Meng
MSc. Candidate, UBC Dept. of Statistics
Inferring population size for epidemiological purposes with the multiplier method
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Abstract: The multiplier method is a method to estimate population size (e.g. the number of sex-workers in a city), popular among epidemiologists. However, it relies on the identity that p_t = N_t/N, where p_t is the proportion of target population with a certain trait, N_t is the number of people with this trait, and N is the size of the target population. This causes problems in today's world where information on many traits exist in record such that each trait can be used to generate an estimate. I will introduce a recent extension of the multiplier method with which information on multiple traits are used simultaneously to produce a single estimate of population size. I will include examples and some theoretical findings on the effect of study design on inference precision.

Room 4192 Earth Sciences Building, 2207 Main Mall
Tue 22nd July 2014
Department of Statistics and Actuarial Science University of Waterloo
Empirical Likelihood Methods for Pretest-Posttest Studies
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Pretest-posttest studies are an important and popular method for assessing treatment effects or the effectiveness of an intervention in many areas of scientific research. There are two distinct features for this type of study: availability of baseline information for all subjects in the study and missingness by design of measures of the responses. In this talk, we first provide a brief overview of existing research on the topic. We then present alternative empirical likelihood approaches to inferences on the treatment effects with efficient use of all available information. Theoretical results are developed, and finite sample performances of the proposed methods with comparison to existing ones are investigated through simulation studies.
This is joint work with Min Chen and Mary Thompson.
Room 4182 Earth Sciences Building, 2207 Main Mall, Vancouver
Tue 15th July 2014
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