Upcoming Meetings
Friday, November 6, 2009 11:00-12:00 pm Room 48-4-H4130 in Lilly Corporate Center
Speaker: Dr. Xin He, University of Maryland
Topic: Semiparametric Analysis of Multivariate Panel Count Data with Application to a Psoriatic Arthritis Study
Abstract: Multivariate panel count data frequently occur in periodic follow-up studies that involve several different types of recurrent events of interest. In many applications, these recurrent event processes can be correlated and it may not be easy to accommodate the dependence structures. In this talk, I will present a class of marginal mean models that leave the dependence structures for related types of recurrent events completely unspecified. Some estimating equations are developed for inference and the resulting estimates of regression parameters are shown to be consistent and asymptotically normal. Simulation studies are conducted for practical situations and the methodology is applied to a motivating cohort study of patients with psoriatic arthritis.
Parking Information
Take South street and turn right (south) onto Alabama street. If you drive close to the building there are several spots of visitor parking on Alabama. Also there are some more visitor parking spaces available in the parking lot on the left side of Alabama. ASA officers will escort non-Lilly people from Bldg 98 lobby to the room where the talk would be (Room 48-3-H4130). We request non-Lilly people to arrive at the 98 lobby by 11:30 pm to allow enough time to get checked in and escorted to the room.
Past 1995-2008 Central Indiana ASA Meetings / Activities
Friday, April 17, 2009 9:00-4:00 pm Rembrandt Salons A&B Lilly Faris Campus at 450 S. Meridian St.
ASA-sponsored shortcourse titled 'Survival Analysis with Correlated or Repeated Endpoints' by Dr. Terry Therneau.
Tuesday, December 12, 2008 2:30-3:30 pm Room 48-3-H3100 in Lilly Corporate Center
Speaker: Dr. Tyler VanderWeele, University of Chicago
Topic: General theory for sufficient cause interactions for dichotomous exposures
Abstract: The sufficient-component cause framework makes reference to the actual causal mechanisms, referred to as sufficient causes, involved in bringing about a dichotomous outcome. When two or more binary causes participate in the same causal mechanism, synergism is said to be present. Synergism sometimes cannot be identified from data; in cases in which data do imply that synergism is present, a sufficient cause interaction is said to be present. It is shown that any set of potential outcomes can, within the sufficient-component cause framework, be replicated by a set of sufficient causes. Empirical and counterfactual conditions are given which imply the presence of an n-way sufficient cause interaction both with and without assumptions of monotonicity. The empirical conditions for sufficient cause interactions are compared with and contrasted to tests for interaction coefficients in linear, log-linear and logistic models. The theory and methods developed in this paper constitute empirical tests for the joint presence of two or more causes in a single causal mechanism.