For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox's proportional hazard model.
In addition, there is relatively little information in the literature on the goodness-of-fit for multiple failure time models.
We carried out a series of simulations to examine the accuracy of the above multiple failure time models in terms of four factors: different sample sizes, censoring levels, numbers of recurrence events and correlation levels.
Analysis of time to onset of action using the multiple failures time model showed superiority of fluticasone/formoterol over fluticasone/salmeterol (hazard ratio: 1.64; 95% CI: 1.28, 2.10; p < 0.001; FAS; see Figure 3 as an example of this effect).
Univariate and multivariate analysis were performed to investigate the effect on outcome (inactivation or relapse) of variables such as age, sex, origin, treatment, cyst size and presence of other echinococcal hepatic cysts using a multiple failure Cox proportional hazard model.
By applying high-order moment standardization technique (HOMST), reliability and sensitivity with single failure mode were obtained and then the reliability model and the sensitivity model with multiple failure modes were developed and common methods such as Narrow bounds, AFOSM and Monte Carlo were used for verification and comparison.
To satisfy the three failure criteria, the plasticity model using multiple failure criteria was implemented.
For nonlinear numerical analysis of concrete, the proposed directionality parameter was employed in the plasticity model with multiple failure criteria, and an identical tension crack parameter was used for both the tensile behavior and compressive behavior of the concrete.
To extend the applicability of the plasticity model to concrete in various stress states, a new model that uses multiple failure criteria was attempted.
However, in this competing risk setting, only cause-specific hazard sub-models for the multiple failure types data have been used.
