Estimation and inference on correlations between biomarkers with repeated measures and left-censoring due to minimum detection levels.

ABSTRACT: Statistical approaches for estimating and drawing inference on the correlation between two biomarkers that are repeatedly assessed over time and subject to left-censoring because minimum detection levels are lacking. We propose a linear mixed-effects model and estimate the parameters with the Monte Carlo expectation maximization (MCEM) method. Inferences regarding the model parameters and the correlation between the biomarkers are performed by applying Louis's method and the delta method. Simulation studies were conducted to compare the proposed MCEM method with existing methods including the maximum likelihood estimation method, the multiple imputation method, and two widely used ad hoc approaches: replacing the censored values with the detection limit or with half of the detection limit.

SUBMITTER: Xie X 

PROVIDER: S-EPMC3875381 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature