"Group sequential procedures based on Ranked Set Sampling, sequential change-point and shrinkage estimation in correlated data"

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In today's golobal village, complex data has become easily available in real-time. This has led to a higher demand in finding efficient statistical methods for estimation and surveillance of parameters governing the data. In this project, I propose efficient methods which incorporate prior nonsample information (such as expert opinion) in the statistical estimation and testing procedures. These methodlogies will improve the ways we tackle analysis of data from clinical trials, longitudinal, spatial and cluster correlated data. A second objective of my proposal is to build statistical methods for the surveillance of parameters based on outcomes that present temporal correlations. These methods have applications in real-time surveillance of infectious diseases, health care performace monitoring and in monitoring financial markets.