Skip to main content

LUP Student Papers

LUND UNIVERSITY LIBRARIES

Bootstrapping methods for assessing causality in survival analysis: A case study on major adverse cardiovascular events

Benthem Ciano, Paulina LU (2023) In Master's Theses in Mathematical Sciences MASM02 20231
Mathematical Statistics
Abstract
The combination of graphical models with Aalen's additive hazards model, resulting in a model known as dynamical path analysis, permits assessing the effects of different variables on times until an event and decomposing these total effects into direct and indirect effects. This thesis proposes novel bootstrapping methods designed for left-truncated right-censored data, conditional on covariates within the framework of Aalen's additive hazards model,
in order to obtain confidence intervals for the estimates.


To illustrate the practical application of the bootstrapping methods, we conduct a case study utilising data from the Malmö diet and cancer study. The data set consists of left-truncated right-censored data.
Our analysis aims... (More)
The combination of graphical models with Aalen's additive hazards model, resulting in a model known as dynamical path analysis, permits assessing the effects of different variables on times until an event and decomposing these total effects into direct and indirect effects. This thesis proposes novel bootstrapping methods designed for left-truncated right-censored data, conditional on covariates within the framework of Aalen's additive hazards model,
in order to obtain confidence intervals for the estimates.


To illustrate the practical application of the bootstrapping methods, we conduct a case study utilising data from the Malmö diet and cancer study. The data set consists of left-truncated right-censored data.
Our analysis aims to examine causality and estimate the direct effects of various covariates on the incidence of major adverse cardiovascular events and indirect effects between covariates.
We compute confidence intervals for these effects with the proposed bootstrapping methods. (Less)
Please use this url to cite or link to this publication:
author
Benthem Ciano, Paulina LU
supervisor
organization
course
MASM02 20231
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Causality, Graphical models, Bootstrap, Survival analysis, Additive hazards model.
publication/series
Master's Theses in Mathematical Sciences
report number
LUNFMS-3119-2023
ISSN
1404-6342
other publication id
2023:E42
language
English
id
9127200
date added to LUP
2023-06-21 10:45:58
date last changed
2023-06-21 14:20:22
@misc{9127200,
  abstract     = {{The combination of graphical models with Aalen's additive hazards model, resulting in a model known as dynamical path analysis, permits assessing the effects of different variables on times until an event and decomposing these total effects into direct and indirect effects. This thesis proposes novel bootstrapping methods designed for left-truncated right-censored data, conditional on covariates within the framework of Aalen's additive hazards model,
in order to obtain confidence intervals for the estimates.


To illustrate the practical application of the bootstrapping methods, we conduct a case study utilising data from the Malmö diet and cancer study. The data set consists of left-truncated right-censored data. 
Our analysis aims to examine causality and estimate the direct effects of various covariates on the incidence of major adverse cardiovascular events and indirect effects between covariates. 
We compute confidence intervals for these effects with the proposed bootstrapping methods.}},
  author       = {{Benthem Ciano, Paulina}},
  issn         = {{1404-6342}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Master's Theses in Mathematical Sciences}},
  title        = {{Bootstrapping methods for assessing causality in survival analysis: A case study on major adverse cardiovascular events}},
  year         = {{2023}},
}