Analysis of quality-of-life adjusted failure time data in the presence of competing, possibly informative, censoring mechanisms |
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| Authors: | Andrea Rotnitzky Andrea Bergesio Andres Farall |
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| Affiliation: | (1) Department of Economics, Universidad Torcuato Di Tella, Sáenz Valiente 1010, Buenos Aires, 1428, Argentina;(2) Department of Biostatistics, Harvard School of Public Health, Boston, USA;(3) Instituto de Calculo, FCEN, Universidad de Buenos Aires, Buenos Aires, Argentina;(4) Departamento de Matemática, FBCB, Universidad Nacional del Litoral, Santa Fe, Argentina;(5) Alma Mater Studiorum, Università di Bologna (Buenos Aires), Bologna, Italy |
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| Abstract: | We derive estimators of the mean of a function of a quality-of-life adjusted failure time, in the presence of competing right censoring mechanisms. Our approach allows for the possibility that some or all of the competing censoring mechanisms are associated with the endpoint, even after adjustment for recorded prognostic factors, with the degree of residual association possibly different for distinct censoring processes. Our methods generalize from a single to many censoring processes and from ignorable to non-ignorable censoring processes. |
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| Keywords: | Cause-specific Dependent censoring Inverse weighted probability Sensitivity analysis |
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