Estimating correlation with multiply censored data arising from the adjustment of singly censored data.

ABSTRACT: Environmental data frequently are left censored due to detection limits of laboratory assay procedures. Left censored means that some of the observations are known only to fall below a censoring point (detection limit). This presents difficulties in statistical analysis of the data. In this paper, we examine methods for estimating the correlation between variables each of which is censored at multiple points. Multiple censoring frequently arises due to adjustment of singly censored laboratory results for physical sample size. We discuss maximum likelihood (ML) estimation of the correlation and introduce a new method (cp.mle2) that, instead of using the multiply censored data directly, relies on ML estimates of the covariance of the singly censored laboratory data. We compare the ML methods

SUBMITTER: Newton E 

PROVIDER: S-EPMC2565512 | biostudies-literature | 2007 Jan

REPOSITORIES: biostudies-literature