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Table 1 Overview of the properties of logistic regression (LR) and the subdistribution models in a time-independent and time-dependent setting

From: Simulation shows undesirable results for competing risks analysis with time-dependent covariates for clinical outcomes

Property Time-independent Time-dependent
  Fine&gray LR Beyersmann & Schumacher LR
Allowance for censoring Yes No Yes No
Accounting for time-to-event Yes No Yes No
Ability to display cumulative incidence functions Yes Only plateau No Only plateau
Interpretation Challenging See text Challenging See text
Probability interpretation Yes Yes No Yes
Dependency on the infection hazard . . Yes No
Simulation performance:     
Ability to capture no effect on cause-specific hazards (α15=α03,α14=α02) Yes Yes No Yes
Ability to capture negative effect on death hazard (α15>α03,α14=α02) Yes Yes Yes, magnitude difficult to interpret Yes
Ability to capture positive effect on death hazard (α15<α03,α14=α02) Yes Yes Questionable Yes
Ability to capture negative effect on discharge hazard (α15=α03,α14<α02) Yes Yes Questionable Yes
Ability to capture positive effect on discharge hazard (α15=α03,α14>α02) Yes Yes Questionable Yes