… hazard regression. The time axis was the difference in days between the day of cancer diagnosis
and … conditional on the diagnosis of lung cancer could also have influenced the results, …

… We checked the PH assumption for each covariate using statistical tests based on the … A
sensitivity analysis was undertaken to investigate the influence of the priors on the posterior …

… diagnostic imaging techniques and genomic platforms for … task in any analysis to avoid the
influence that some feature … This study has shown that Naive Bayes outperforms the SVM and …

… An application to survival analysis shows that the GOLLEx distribution provides much …
influential observation(s) for the analysis we use the Bayesian case-deletion influence diagnostic …

… Several tools are notably available for convergence diagnosis of Stan HMC estimated models
(eg … relationships that could have appeared to influence the work reported in this paper. …

… the important variables that influence tuberculosis disease. … The use of likelihood ratio
tests is commonly thought to be … , Akaike information criterion and the Bayesian information …

… In the frequentist and Bayesian stress tests using coefficient … the influence of additional
useful information, model selection… In this paper, we use discrete time hazard analysis to model …

… However, rare studies have investigated the combined influence … maximum log-rank risk
tests are nominated and randomly … DeepSurv model, configured with Bayesian hyperparameter …

… of analysis exceeding that of previous studies. Using recent computational advances in
Bayesian survival analysis, this paper models the … Fortunately, the Bayesian approach provides a …

… , is a frequently used model in survival analysis and can be … Bayesian control chart based
on the Hidden Markov Model (… , greater values might influence the model substantially. This …