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Journal of Thoracic Oncology : Official Publication of the International Association for the Study of Lung Cancer
|
November 18, 2011
Random Survival Forests
Jeremy M G Taylor
Lifetime Data Analysis
|
May 12, 2010
Discussion of "Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches", by Hanson, Branscum and Johnson
Jeremy M G Taylor
Biometrics
|
September 7, 2016
Residual-based model diagnosis methods for mixture cure models
Yingwei Peng, Jeremy M G Taylor
Statistics in Medicine
|
January 8, 2011
Mixture cure model with random effects for the analysis of a multi-center tonsil cancer study
Yingwei Peng, Jeremy M G Taylor
Statistics in Medicine
|
January 25, 2024
Optimizing dynamic predictions from joint models using super learning
Dimitris Rizopoulos, Jeremy M G Taylor
Controlled Clinical Trials
|
December 31, 2002
Surrogate markers and joint models for longitudinal and survival data
Jeremy M G Taylor, Yan Wang
Biometrics
|
December 24, 2002
A measure of the proportion of treatment effect explained by a surrogate marker
Yue Wang, Jeremy M G Taylor
Statistics in Medicine
|
November 11, 2008
Nonparametric comparison of two survival functions with dependent censoring via nonparametric multiple imputation
Chiu-Hsieh Hsu, Jeremy M G Taylor
Biostatistics (Oxford, England)
|
April 17, 2009
Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach
Cécile Proust-Lima, Jeremy M G Taylor
Biostatistics (Oxford, England)
|
March 28, 2018
EM algorithms for fitting multistate cure models
Lauren J Beesley, Jeremy M G Taylor
Page
of 22
Search research articles
Search
Showing results (1-10 of 213) with videos related to
Sort By:
Page
of 22
Journal of Thoracic Oncology : Official Publication of the International Association for the Study of Lung Cancer
|
November 18, 2011
Random Survival Forests
Jeremy M G Taylor
Lifetime Data Analysis
|
May 12, 2010
Discussion of "Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches", by Hanson, Branscum and Johnson
Jeremy M G Taylor
Biometrics
|
September 7, 2016
Residual-based model diagnosis methods for mixture cure models
Yingwei Peng, Jeremy M G Taylor
Statistics in Medicine
|
January 8, 2011
Mixture cure model with random effects for the analysis of a multi-center tonsil cancer study
Yingwei Peng, Jeremy M G Taylor
Statistics in Medicine
|
January 25, 2024
Optimizing dynamic predictions from joint models using super learning
Dimitris Rizopoulos, Jeremy M G Taylor
Controlled Clinical Trials
|
December 31, 2002
Surrogate markers and joint models for longitudinal and survival data
Jeremy M G Taylor, Yan Wang
Biometrics
|
December 24, 2002
A measure of the proportion of treatment effect explained by a surrogate marker
Yue Wang, Jeremy M G Taylor
Statistics in Medicine
|
November 11, 2008
Nonparametric comparison of two survival functions with dependent censoring via nonparametric multiple imputation
Chiu-Hsieh Hsu, Jeremy M G Taylor
Biostatistics (Oxford, England)
|
April 17, 2009
Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach
Cécile Proust-Lima, Jeremy M G Taylor
Biostatistics (Oxford, England)
|
March 28, 2018
EM algorithms for fitting multistate cure models
Lauren J Beesley, Jeremy M G Taylor
Page
of 22