Interval-Censored Regression with Non-Proportional Hazards with Applications
Stats, 2023 Proportional hazards models and, in some situations, accelerated failure time models, are not suitable for analyzing data when the failure ratio between two individuals is not constant. We present a Weibull accelerated failure time model with covariables
Fábio Prataviera +4 more
doaj +2 more sources
A Comparison of Statistical Methods for Time-To-Event Analyses in Randomized Controlled Trials Under Non-Proportional Hazards. [PDF]
Stat MedWhile well‐established methods for time‐to‐event data are available when the proportional hazards assumption holds, there is no consensus on the best inferential approach under non‐proportional hazards (NPH).
Klinglmüller F +12 more
europepmc +2 more sources
A simulation‐free group sequential design with max‐combo tests in the presence of non‐proportional hazards [PDF]
Pharmaceutical statistics, 2021 Non‐proportional hazards (NPH) have been observed in many immuno‐oncology clinical trials. Weighted log‐rank tests (WLRT) with suitable weights can be used to improve the power of detecting the difference between survival curves in the presence of NPH ...
Lili Wang, Xiaodong Luo, Cheng Zheng
openalex +3 more sources
Non‐proportional hazards in immuno‐oncology: Is an old perspective needed? [PDF]
Pharmaceutical Statistics, 2020 A fundamental concept in two‐arm non‐parametric survival analysis is the comparison of observed versus expected numbers of events on one of the treatment arms (the choice of which arm is arbitrary), where the expectation is taken assuming that the true ...
D. Magirr
semanticscholar +5 more sources
Application of random survival forests in understanding the determinants of under-five child mortality in Uganda in the presence of covariates that satisfy the proportional and non-proportional hazards assumption. [PDF]
BMC Res Notes, 2017 BackgroundUganda just like any other Sub-Saharan African country, has a high under-five child mortality rate. To inform policy on intervention strategies, sound statistical methods are required to critically identify factors strongly associated with ...
Nasejje JB, Mwambi H.
europepmc +3 more sources
BMJ, 2017 The hazard ratio (HR) is the most common measure of treatment effect in clinical trials that use time-to-event outcomes such as survival. When survival curves cross over or separate only after a considerable time, the proportional hazards assumption of ...
Dehbi HM, Royston P, Hackshaw A.
europepmc +2 more sources
, 2018 The Cox proportional hazard model is being used extensively in oncology in studying the relationship between survival times and prognostic factors. The main question that needs to be addressed with respect to the applicability of the Cox PH model is ...
Muditha Perera, Chris P. Tsokos
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Estimation of treatment effect under non‐proportional hazards and conditionally independent censoring [PDF]
Statistics in Medicine, 2012 In clinical trials with time‐to‐event outcomes, it is common to estimate the marginal hazard ratio from the proportional hazards model, even when the proportional hazards assumption is not valid. This is unavoidable from the perspective that the estimator must be specified a priori if probability statements about treatment effect estimates are desired.
Adam P. Boyd +2 more
semanticscholar +5 more sources
Non-proportional hazards model with a PVF frailty term: application with a melanoma dataset. [PDF]
J Appl StatRosa KC, Calsavara VF, Louzada F.
europepmc +3 more sources
Clinical effectiveness reporting of novel cancer drugs in the context of non-proportional hazards: a review of nice single technology appraisals. [PDF]
Int J Technol Assess Health Care, 2023 Salmon D, Melendez-Torres GJ.
europepmc +3 more sources