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Title: Regression analysis for censored and truncated event data using pseudo-observations Authors:  Erik Parner - Aarhus University (Denmark) [presenting]
Abstract: The pseudo-observation method has become popular for performing regression analysis for censored event data. Pseudo-observations are transformations of the event data; once they are computed, they can be treated as observations for regression analysis, and often standard statistical software can be used for the analysis. Applications include regression analysis for cumulative risk, restricted means and number of life years lost due to specific causes of death. We discuss under which conditions we may expect the pseudo-observation method to provide unbiased estimates. In particular, we consider regression models for cumulative risk in a cohort with left truncation. Some variants of pseudo-observations are also discussed.