• The Korean Journal of Applied Statistics
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• v.37 no.6
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• pp.769-782
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• 2024

In many biomedical fields, especially in studies of disease progressions, we frequently encounter two sequential events, both of which are often interval-censored due to regular examinations. Such a structure is called doubly interval-censoring (DIC), and our primary interest is the elapsed time between two consecutive events. In this paper, we propose a weighted rank regression approach for DIC data under the semiparametric accelerated failure time model. After transforming DIC data into simple interval-censored data where the true elapsed times may lie, we develop estimation procedures with a Gehan-type weight by gathering all comparable pairs of observed residuals from transformed data. Moreover, we generalize this approach with data-dependent weights and extend it to clustered DIC data, where the cluster size is potentially informative, using an inverse weighting strategy. An efficient technique for variance estimation as an alternative to resampling techniques is considered. We establish asymptotic properties and conduct numerical studies to demonstrate finite sample performances. Finally, we illustrate our method with a real dataset for clustered DIC data.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.113-127
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• 1998

There have been a great deal of interests in comparing two survival distributins in clinical trials. This paper compares some well-known statistical methods for testing the equality of two survival distributions. Simulation studies also provide some insights into the properties of these test statistics across several types of survival distributions and degrees of censorship.

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.95-108
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• 1996

There are many clinical trials where a large portion of the patients are cured of disease. In such a case, one might be more interested in testing the differences in cure rates rather than other types of differences in failure distribution. For ethical and economic reasons, clinical trials must be repeatedly monitored for evidence of treatment benefit or harm. In this article, we examined by simulation the properties of nonparametric group sequential methods for comparing the cure rates between two treatment groups during the trial in a wide range of alternatives, censoring rates and cure rates.