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Jane-Ling Wang

Showing results (1-10 of 63) with videos related to

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Journal of the American Statistical Association|June 27, 2022
Mean and Covariance Estimation for Functional SnippetsZhenhua Lin, Jane-Ling Wang
Journal of the Royal Statistical Society. Series B, Statistical Methodology|July 31, 2023
Testing homogeneity: the trouble with sparse functional dataChangbo Zhu, Jane-Ling Wang
Biometrics|September 25, 2007
Modeling longitudinal data with nonparametric multiplicative random effects jointly with survival dataJimin Ding, Jane-Ling Wang
Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability|July 31, 2012
The central limit theorem under random truncationWinfried Stute, Jane-Ling Wang
Journal of the American Statistical Association|August 7, 2012
Semiparametric Efficient Estimation for a Class of Generalized Proportional Odds Cure ModelsMeng Mao, Jane-Ling Wang
Brain Connectivity|June 21, 2019
A New Approach for Functional Connectivity via Alignment of Blood Oxygen Level-Dependent SignalsChun-Jui Chen, Jane-Ling Wang
Annals of Statistics|February 27, 2018
MODELING LEFT-TRUNCATED AND RIGHT-CENSORED SURVIVAL DATA WITH LONGITUDINAL COVARIATESYu-Ru Su, Jane-Ling Wang
Annals of Statistics|March 13, 2018
SEMIPARAMETRIC EFFICIENT ESTIMATION FOR SHARED-FRAILTY MODELS WITH DOUBLY-CENSORED CLUSTERED DATAYu-Ru Su, Jane-Ling Wang
Biostatistics (Oxford, England)|April 29, 2014
Standard error estimation using the EM algorithm for the joint modeling of survival and longitudinal dataCong Xu, Paul D Baines, Jane-Ling Wang
Biometrics|December 13, 2006
Joint modeling of survival and longitudinal data: likelihood approach revisitedFushing Hsieh, Yi-Kuan Tseng, Jane-Ling Wang
Pageof 7

Showing results (1-10 of 63) with videos related to

Sort By:
Pageof 7
Journal of the American Statistical Association|June 27, 2022
Mean and Covariance Estimation for Functional SnippetsZhenhua Lin, Jane-Ling Wang
Journal of the Royal Statistical Society. Series B, Statistical Methodology|July 31, 2023
Testing homogeneity: the trouble with sparse functional dataChangbo Zhu, Jane-Ling Wang
Biometrics|September 25, 2007
Modeling longitudinal data with nonparametric multiplicative random effects jointly with survival dataJimin Ding, Jane-Ling Wang
Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability|July 31, 2012
The central limit theorem under random truncationWinfried Stute, Jane-Ling Wang
Journal of the American Statistical Association|August 7, 2012
Semiparametric Efficient Estimation for a Class of Generalized Proportional Odds Cure ModelsMeng Mao, Jane-Ling Wang
Brain Connectivity|June 21, 2019
A New Approach for Functional Connectivity via Alignment of Blood Oxygen Level-Dependent SignalsChun-Jui Chen, Jane-Ling Wang
Annals of Statistics|February 27, 2018
MODELING LEFT-TRUNCATED AND RIGHT-CENSORED SURVIVAL DATA WITH LONGITUDINAL COVARIATESYu-Ru Su, Jane-Ling Wang
Annals of Statistics|March 13, 2018
SEMIPARAMETRIC EFFICIENT ESTIMATION FOR SHARED-FRAILTY MODELS WITH DOUBLY-CENSORED CLUSTERED DATAYu-Ru Su, Jane-Ling Wang
Biostatistics (Oxford, England)|April 29, 2014
Standard error estimation using the EM algorithm for the joint modeling of survival and longitudinal dataCong Xu, Paul D Baines, Jane-Ling Wang
Biometrics|December 13, 2006
Joint modeling of survival and longitudinal data: likelihood approach revisitedFushing Hsieh, Yi-Kuan Tseng, Jane-Ling Wang
Pageof 7