Marginal proportional hazards models for multivariate interval-censored data
Biometrika. 2023 Sep;110(3):815-830. doi: 10.1093/biomet/asac059. Epub 2022 Nov 2.ABSTRACTMultivariate interval-censored data arise when there are multiple types of events or clusters of study subjects, such that the event times are potentially correlated and when each event is only known to occur over a particular time interval. We formulate the effects of potentially time-varying covariates on the multivariate event times through marginal proportional hazards models while leaving the dependence structures of the related event times unspecified. We construct the nonparametric pseudolikelihood under the working assumption ...
Source: Biometrika - August 21, 2023 Category: Biotechnology Authors: Yangjianchen Xu Donglin Zeng D Y Lin Source Type: research
Marginal proportional hazards models for multivariate interval-censored data
Biometrika. 2023 Sep;110(3):815-830. doi: 10.1093/biomet/asac059. Epub 2022 Nov 2.ABSTRACTMultivariate interval-censored data arise when there are multiple types of events or clusters of study subjects, such that the event times are potentially correlated and when each event is only known to occur over a particular time interval. We formulate the effects of potentially time-varying covariates on the multivariate event times through marginal proportional hazards models while leaving the dependence structures of the related event times unspecified. We construct the nonparametric pseudolikelihood under the working assumption ...
Source: Biometrika - August 21, 2023 Category: Biotechnology Authors: Yangjianchen Xu Donglin Zeng D Y Lin Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
Fast and powerful conditional randomization testing via distillation
Biometrika. 2022 Jun;109(2):277-293. doi: 10.1093/biomet/asab039. Epub 2021 Jul 8.ABSTRACTWe consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y⫫X∣Z. The conditional randomization test was recently proposed as a way to use distributional information about X∣Z to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about Y∣(X,Z). This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statist...
Source: Biometrika - July 7, 2023 Category: Biotechnology Authors: Molei Liu Eugene Katsevich Lucas Janson Aaditya Ramdas Source Type: research
