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Original Articles

Likelihood-based inference for the transmuted log-logistic model in the presence of right-censored data

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Pages 1798-1813 | Received 07 Nov 2017, Accepted 06 Feb 2018, Published online: 06 Mar 2018
 

ABSTRACT

Although new transmuted distributions have been widely proposed in the last few years, it is rarely to find those class of models applied in survival analysis in the presence of censored lifetimes. In this context, we are concerned in applying the transmuted log-logistic model in the study of discharge times of patients treated with the Linezolid drug. For model fitting, we use and compare different profile likelihood methods. Analysis of residuals and influence are also presented. All results are validated in a simulation study by considering the bootstrap techniques.

MATHEMATICS SUBJECT CLASSIFICATION:

Notes

1 Here, t(r) represents the fixed time of end of study (Type-I censoring scheme).

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