… make use, to train the neural network, of the classical Cox partial likelihood and base their
analysis on the proportional hazard … We use the R package Timereg and the Python package …

… by providing a condensed compendium of competing risks survival methods with a unified
… are available as R or Python packages, other methods are only accessible through ad hoc …

… The latter three references show how these ideas can clarify competing risks analysis by
introducing a new estimand. Under the appropriate assumptions that will be outlined in later sec…

… Analyzing competing risk data using the R timereg package.  … study sites, 20 and analyses
of cardiovascular mortality accounted for the competing risk of noncardiovascular mortality. …

… any competing risks distribution. Finally, we apply our proposed algorithm to analyze a
well-known melanoma data. … that is available in the “timereg” package of R software. The dataset …

… In competing risk settings our methods can be used to make nonparametric inference for the
effects on multiple … Analyzing competing risk data using the R timereg package. J. Statist. …

… Finally, in Section 7, we test the new method on data from an AIDS cohort and on a cohort of
… data are publicly available in the timereg R package 40 and has previously been analyzed …

… epidemiologic data, and cmprsk the and timereg packages for … -analysis, and this could be
explained by the inclusion of a greater number of risk factors or the control of competing risks …

… analysis, it is often the case that we may not have exact failure times for all observations, as
lifetime data … We can then fit a mob-type tree with the function lmtree in the R package partykit…

… curve and the Cox regression analysis, whereas the “timereg” and “cmprsk” packages were
… as the competing risk, we further conducted the Fine and Gray’s regression analysis (Table 4…