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Multiple-fraction treatments were correlated using the linear quadratic and linear quadratic-linear/universal survival models.
The SI score outperformed tumor grade and pleural invasion in univariate (Table 2) and/or multivariate survival models (Table 3).
Reversal of adaptive behaviors (e.g. window closing) was modeled with deadband models or survival models.
To account for non-linear relationships, we apply non-parametric survival models with P-splines.
All survival models were checked for proportionality.
This model has advantages over other survival models (Allison 1995).
Table 2 Some selected cure rate survival models S.No.
Imaging descriptors improve the predictive power of survival models for glioblastoma patients.
Anderson-Gill recurrent events survival models and generalized estimating equations were used to assess predictive validity.
Study Design: We used a longitudinal, population-based design with maximum likelihood estimation of survival models.
Condit et al. ([2006]) used Bayesian hierarchical growth and survival models and provides further details.
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