Comparison of Cox Proportional Hazards Model and Lognormal Accelerated Failure Time Model: Application in Time to Event Analysis of Acute Liver Failure Patients in India
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چکیده
منابع مشابه
Monitoring Lognormal Reliability Data in a Two-Stage Process Using Accelerated Failure Time Model
The reliability data is getting used to monitor and improve the quality of products or services. Nowadays, most of products or services are the results of processes with dependent stages referred to as multi-stage process. In these processes, the quality characteristics are affected by the quality characteristics in the previous stages, called as cascade property. In some cases, it is not possi...
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Background: Thalassemia major (TM) is a severe disease and the most common anemia worldwide. The survival time of the disease and its risk factors are of importance for physicians. The present study was conducted to apply the semi-parametric Cox PH model and use parametric proportional hazards (PH) and accelerated failure time (AFT) models to identify the risk factors related to survival of TM ...
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The eld of survival analysis has experienced tremendous growth during the latter half of the 20th century. The methodological developments of survival analysis that have had the most profound impact are the Kaplan-Meier method for estimating the survival function, the log-rank test for comparing the equality of two or more survival distributions, and the Cox proportional hazards (PH) model for...
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A unified implementation of parametric proportional hazards (PH) and accelerated failure time (AFT) models for right-censored or intervalcensored and left-truncated data is described. The description here is válid for time-constant covariates, but the necessary modifications for handling time-varying covariates are implemented in eha. Note that only piecewise constant time variation is handled.
متن کاملTime-dependent covariates in the Cox proportional-hazards regression model.
The Cox proportional-hazards regression model has achieved widespread use in the analysis of time-to-event data with censoring and covariates. The covariates may change their values over time. This article discusses the use of such time-dependent covariates, which offer additional opportunities but must be used with caution. The interrelationships between the outcome and variable over time can ...
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ژورنال
عنوان ژورنال: Nepalese Journal of Statistics
سال: 2019
ISSN: 2645-839X,2565-5213
DOI: 10.3126/njs.v3i0.25576