Sentence examples for multivariate failure or from inspiring English sources

The majority of existing regression methods for analyzing multivariate failure or recurrent event time data assumes multiplicative covariate effects.

In general, standard hazard regression methods cannot be applied because of correlations between multivariate failure or recurrent event times within a subject.

Sequentially ordered multivariate failure time or recurrent event duration data are commonly observed in biomedical longitudinal studies.

Sequentially ordered multivariate failure time data or recurrent event time data are commonly observed in biomedical longitudinal studies.

Multivariate analysis revealed that hematologic failure (OR 8.6, p = 0.04) and cardiovascular failure (OR 7.6, p = 0.06) independently predicted death.

Multivariate analysis revealed that hematologic (OR 8.4, p =.025) and cardiovascular failure (OR 7.5, p = 032) independently predicted death.

Multivariate analysis identified heart failure (odds ratio [OR] 3.3, 95% confidence interval [CI] 1.6 to 6.8), renal failure (OR 2.5, 95% CI 1.2 to 5.2), and co-morbidity (OR 2.4, 95% CI 1.1 to 5.1) as independent risk factors for death.

Topics include censoring, Kaplan-Meier estimation, logrank test, proportional hazards regression, accelerated failure time model, multivariate failure time analysis and competing risks.

Further, it is worthy extending our approach to model multivariate failure time.

Fan and Wang (2009), Liu et al. (2010) used the same approach for multivariate failure time data with auxiliary covariates.

As stressed in [24], the multivariate mrl is particularly useful in modeling and analyzing multivariate failure data when there is a lack of independence among the components (lifetimes).