Statistical analysis with missing data
Statistical analysis with missing data
Improving the estimation of Kendall's tau when censoring affects only one of the variables
Computational Statistics & Data Analysis
Estimation of Kendall's tau from censored data
Computational Statistics & Data Analysis
| Hi-index | 0.03 |
This paper extends the permutation procedures for truncated data in Diaconis et al. (http://www-stat.stanford.edu/~susan/.) to doubly censored data. As in Diaconis et al. (http://www-stat.stanford.edu/~susan/.), the proposed procedure is based on samples from the conditional distribution of rank statistics which is uniformly distributed on a set of permutations. Subsequently, our procedure is applied to testing independence with bivariate censored data and estimating a regression coefficient with doubly censored data. Also, when estimating a regression coefficient with doubly censored data, simulation studies show that the proposed procedure is superior to that of Akritas et al. (J. Amer. Statist. Assoc. 90 (1995) 170).