Reference number : GC-2017-Q1-02269, amendment number : , agreement type : G, recipient legal name : Lakhal-Chaieb, Lajmi (Université Laval), recipient country : CA, recipient province : nan, recipient city : Quebec|Québec, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Hierarchical survival data arise when medical studies yield multiple correlated survival outcomes per individual in family-based design. This setting involves between- and within-individuals dependencies. Modelling, estimating and understanding the between- and within-individuals dependencies is of prime interest to many practitioners. In the first part of this project, we will propose, and compare copula-based approaches to model these dependencies. We will express risk prediction functions that assess the odds of experiencing a future even given the information available at some point in terms of these dependence structures. We will provide a guideline to help the users choose which strategy is more appropriate for their data. We will derive inference procedures to estimate and test the quantities of interest derived from these models using standard right-censored observations in the presence of a selection bias. In the second part of this project, we will derive procedures to test the association between a set of genetic covariates containing common and rare variants and multiple survival outcomes in the presence of familial dependencies. We will investigate several strategies to assess the significance of the derived tests. In the last part of the project, we will generalize association test to assess the effect of covariates on the correlation between survival outcomes., program purpose french : Hierarchical survival data arise when medical studies yield multiple correlated survival outcomes per individual in family-based design. This setting involves between- and within-individuals dependencies. Modelling, estimating and understanding the between- and within-individuals dependencies is of prime interest to many practitioners. In the first part of this project, we will propose, and compare copula-based approaches to model these dependencies. We will express risk prediction functions that assess the odds of experiencing a future even given the information available at some point in terms of these dependence structures. We will provide a guideline to help the users choose which strategy is more appropriate for their data. We will derive inference procedures to estimate and test the quantities of interest derived from these models using standard right-censored observations in the presence of a selection bias. In the second part of this project, we will derive procedures to test the association between a set of genetic covariates containing common and rare variants and multiple survival outcomes in the presence of familial dependencies. We will investigate several strategies to assess the significance of the derived tests. In the last part of the project, we will generalize association test to assess the effect of covariates on the correlation between survival outcomes., agreement title english : Genetics applications in multivariate survival analysis, agreement title french : Genetics applications in multivariate survival analysis, agreement number : RGPIN, agreement value : 150000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada