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The assumption of proportional hazards assumed in the Cox proportional hazards model was assessed graphically.
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Parametric proportional hazard models with the baseline hazard assumed to be constant across time was found to well describe the OS or PFS profiles after paclitaxel treatment.
In the above expression H ∗(t) is the expected cumulative hazard in a comparable group from the background population and assumed known whereas Θ t) is the cumulative excess hazard assumed to be attributable to the cancer.
The Cox model specifies the hazard of a patient i as λ i (t ) = λ 0(t )exp(β pclust j ), where λ0 t) is the baseline hazard assumed to be equal for all patients (proportional hazards), and pclust j is the jth pclust of patient i.
This model fits the hazard, assuming an exponential function of the summation of the regression coefficients b1,…,bk.
In scenario 1, the occurrence probability of hazards is assumed equal everywhere in the whole country, that is, hazards follow a uniform spatial distribution.
Even in simple additive models where constant hazards were assumed, we saw a good agreement between additive and proportional hazards models.
The hazards are assumed to be constant within pre-specified sub intervals of follow-up time (that is, piecewise constant hazards).
For these models, the BRCA1 and BRCA2 relative hazards were assumed to be constant within each 10-year interval: 20 29, 30 39, 40 49, 50 59 and 60 69 years.
The analysis was carried out using a proportional hazards model (assumed to be either the Weibull model or a grouped data model) with the Survival Kit v6 program package [ 11].
In relative survival, the total mortality hazard is assumed to consist of the general population mortality hazard and of an excess hazard which is attributable to cancer.
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CEO of Professional Science Editing for Scientists @ prosciediting.com