Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Heteroscedastic Accelerated Failure Time Model for Survival Analysis   Nonparametric and semiparametric methods are commonly used in survival
analysis to mitigate the bias due to model misspecification. However, such
methods often cannot estimate upper-tail survival quantiles when a sizable
proportion of the data are censored, in which case parametric likelihood-based
estimators present a viable alternative. In this article, we extend a popular
family of parametric survival models which make the Accelerated Failure Time
(AFT) assumption to account for heteroscedasticity in the survival times. The
conditional variances can depend on arbitrary covariates, thus adding
considerable flexibility to the homoscedastic model. We present an
Expectation-Conditional-Maximization (ECM) algorithm to efficiently compute the
HAFT maximum likelihood estimator with right-censored data. The methodology is
applied to the heavily censored data from a colon cancer clinical trial, for
which a new type of highly stringent model residuals is proposed. Based on
these, the HAFT model was found to eliminate most outliers from its
homoscedastic counterpart.

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The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
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The categories of this paper are: eess
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The categories of this paper are: hep-th
18
The categories of this paper are: econ
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The categories of this paper are: mtrl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: nlin
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The categories of this paper are: quant-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: q-alg
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The categories of this paper are: comp-gas
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The categories of this paper are: acc-phys
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The categories of this paper are: alg-geom