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Found 3 papers, 0 papers with code
A Multiple kernel testing procedure for non-proportional hazards in factorial designs
In this paper we propose a Multiple kernel testing procedure to infer survival data when several factors (e. g. different treatment groups, gender, medical history) and their interaction are of interest simultaneously.
Hypothesis testing for matched pairs with missing data by maximum mean discrepancy: An application to continuous glucose monitoring
A frequent problem in statistical science is how to properly handle missing data in matched paired observations.
A kernel test for quasi-independence
We consider settings in which the data of interest correspond to pairs of ordered times, e. g, the birth times of the first and second child, the times at which a new user creates an account and makes the first purchase on a website, and the entry and survival times of patients in a clinical trial.
