Biological Sciences : 120
Date & Time
February 19, 2014, 11:00 am – 12:00 pm
- Sufficient Dimension Reduction with Cook's PFC in the Presence of Categorical Predictors
- Most methodologies for sufficient dimension reduction (SDR) in regression are limited to continuous predictors. However, a very large number of actual data sets do contain variables of both continuous and categorical types. Application of these methods to regressions that include qualitative predictors such as gender or species may be inappropriate. We consider regressions that include a set of qualitative predictors W in addition to a vector X of many-valued predictors and a response Y. Using principal fitted components (PFC) models, a likelihood-based SDR method, we seek the sufficient dimension reduction of X that is constrained through the sub-populations established by W. We provide the estimator of the sufficient reduction subspace and demonstrate how it works through application to an existing dataset. As the need is arising for effective analysis strategies for high-dimensional data, the results we present significantly widen the applicative scope of PFC for sufficient dimension reduction.
- Basic Concepts of Cost-Effectiveness Analysis (CEA)
- Cost effectiveness analysis is now an integral part of health technology assessment and addresses the question of whether a new treatment or other health care intervention offers good value of money. This talk generally aims to introduce the basic framework of Cost-Effectiveness Analysis (CEA) in the context of a 2-arm Randomized Clinical Trial (RCT). The structure of the talk begins with the five key parameters of CEA along with some measures of effectiveness and cost. The cost-effectiveness (CE) plane, the Incremental Cost-Effectiveness Ratio (ICER) and the Incremental Net Benefit (INB) are then conscripted for decision making, followed by an example in order to illustrate the aforementioned. Finally, statistical aspects and problems are briefly touched upon.