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Kjetil Røysland

Showing results (1-10 of 22) with videos related to

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Biometrics|June 22, 2019
On null hypotheses in survival analysisMats J Stensrud, Kjetil Røysland, Pål C Ryalen
BMJ Open|January 10, 2014
Comparative effectiveness study on human papillomavirus detection methods used in the cervical cancer screening programmeMari Nygård, Kjetil Røysland, Suzanne Campbell, et al.
Epidemiology (Cambridge, Mass.)|January 5, 2019
Sufficient Cause Interaction for Time-to-event OutcomesMats Julius Stensrud, Pål Christie Ryalen, Kjetil Røysland
Lifetime Data Analysis|February 25, 2019
The additive hazard estimator is consistent for continuous-time marginal structural modelsPål C Ryalen, Mats J Stensrud, Kjetil Røysland
Epidemiology (Cambridge, Mass.)|March 1, 2017
Exploring Selection Bias by Causal Frailty Models: The Magnitude MattersMats Julius Stensrud, Morten Valberg, Kjetil Røysland, et al.
Biostatistics (Oxford, England)|August 21, 2018
Causal inference in continuous time: an example on prostate cancer therapyPål Christie Ryalen, Mats Julius Stensrud, Sophie Fosså, et al.
Journal of the Royal Statistical Society. Series A, (Statistics in Society)|November 30, 2012
Causality, mediation and time: a dynamic viewpointOdd O Aalen, Kjetil Røysland, Jon Michael Gran, et al.
Lifetime Data Analysis|July 14, 2010
Recurrent events and the exploding Cox modelHåkon K Gjessing, Kjetil Røysland, Edsel A Pena, et al.
Biostatistics (Oxford, England)|September 24, 2021
Prognosis of cancer survivors: estimation based on differential equationsPål C Ryalen, Bjørn Møller, Christoffer H Laache, et al.
Statistics in Medicine|August 18, 2015
Dynamic path analysis - a useful tool to investigate mediation processes in clinical survival trialsSusanne Strohmaier, Kjetil Røysland, Rune Hoff, et al.
Pageof 3

Showing results (1-10 of 22) with videos related to

Sort By:
Pageof 3
Biometrics|June 22, 2019
On null hypotheses in survival analysisMats J Stensrud, Kjetil Røysland, Pål C Ryalen
BMJ Open|January 10, 2014
Comparative effectiveness study on human papillomavirus detection methods used in the cervical cancer screening programmeMari Nygård, Kjetil Røysland, Suzanne Campbell, et al.
Epidemiology (Cambridge, Mass.)|January 5, 2019
Sufficient Cause Interaction for Time-to-event OutcomesMats Julius Stensrud, Pål Christie Ryalen, Kjetil Røysland
Lifetime Data Analysis|February 25, 2019
The additive hazard estimator is consistent for continuous-time marginal structural modelsPål C Ryalen, Mats J Stensrud, Kjetil Røysland
Epidemiology (Cambridge, Mass.)|March 1, 2017
Exploring Selection Bias by Causal Frailty Models: The Magnitude MattersMats Julius Stensrud, Morten Valberg, Kjetil Røysland, et al.
Biostatistics (Oxford, England)|August 21, 2018
Causal inference in continuous time: an example on prostate cancer therapyPål Christie Ryalen, Mats Julius Stensrud, Sophie Fosså, et al.
Journal of the Royal Statistical Society. Series A, (Statistics in Society)|November 30, 2012
Causality, mediation and time: a dynamic viewpointOdd O Aalen, Kjetil Røysland, Jon Michael Gran, et al.
Lifetime Data Analysis|July 14, 2010
Recurrent events and the exploding Cox modelHåkon K Gjessing, Kjetil Røysland, Edsel A Pena, et al.
Biostatistics (Oxford, England)|September 24, 2021
Prognosis of cancer survivors: estimation based on differential equationsPål C Ryalen, Bjørn Møller, Christoffer H Laache, et al.
Statistics in Medicine|August 18, 2015
Dynamic path analysis - a useful tool to investigate mediation processes in clinical survival trialsSusanne Strohmaier, Kjetil Røysland, Rune Hoff, et al.
Pageof 3