Flexible Statistical Methods for Complex Structured Data Analysis

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Complex structured data emerge from many fields including medical, industrial and environmental studies. Consequently, there is an urgent need for developing powerful statistical methods to enable more efficient use of information, and to analyze data using more flexible statistical models. One of the most challenging statistical issues is identification of the relationship between outcomes and risk factors, and ultilization of the resulting models for outcome prediction. Extensive research attention has been directed to this area and there has been a rapid growth in the literature using either semi-parametric or nonparametric approaches, but flexible approaches to incorporate various types of risk effects are still in great demand.