Biostatistics Seminar Series - Jing Lei, PhD

Title: A Two Sample Conditional Distribution Test Using Conformal PredictionAbstract: We consider the problem of testing the equality of the conditional distribution of a response variable given a set of covariates between two populations. Such a two-sample conditional distribution test is related to transfer learning and causal inference. We develop a nonparametric two-sample conditional distribution test using the conformal prediction framework. The construction of our test statistic combines recent developments in conformal prediction with a novel choice of conformity score, resulting in a valid and powerful test statistic under very general settings. To our knowledge, this is the first successful attempt of using conformal prediction for testing statistical hypotheses beyond exchangeability. Our method is suitable for modern machine learning scenarios where the data has high dimensionality and large sample sizes, and can be effectively combined with existing classification algorithms to find good conformity score functions. The performance of the proposed method is demonstrated in synthetic and real data examples.