Only when the test for interactions was significant (P < 0.05), we looked at the pair-wise hazard ratios for assessing effects of interacting variables.
We undertook multivariate analyses of survival using a step-wise Cox proportional hazard model and Kaplan Meier analysis.
For both tasks, we fit to choice data a version of the normative model that ignored the block-wise changes in objective hazard rate.
A step-wise Cox proportional hazards regression model was used for multivariate analysis.
We looked for independent risk factors of P. aeruginosa acquisition by means of a step-wise Cox proportional hazards model.
Alternatively, we estimated the model with a piece-wise constant specification of the baseline hazard to allow for greater flexibility.
To determine the smallest number of parameters that could jointly predict disease recurrence in our cohort of patients, the Cox proportional hazard model and step-wise selection analysis was used.
Multivariate analysis was performed by using Cox's proportional hazard regression test in step-wise mode.
To identify independent factors significantly related to patient prognosis, we used Cox proportional hazard analysis with a step-wise forward procedure.
A test for proportional hazards using the Schoenfeld residuals was performed, and for covariates indicating evidence of non-proportionality, spline smooth estimates of time-dependent hazard ratios (HRs) with point-wise confidence bands were calculated [ 32].
(18, 19) Point-wise 95% confidence intervals (CI) for the relative hazard have been calculated by bootstrap resampling with 1000 repetitions.
