A profile likelihood based method of estimation and inference on the correlation coefficient
of bivariate data with different types of censoring and missingness.
Imputations of missing values using the Sequential Regression (also known as Chained
Equations) Method. Multiple imputation analyses for both descriptive and model-based
analysis. Analysis that accounts for complex design features, weighting, clustering
and stratification.
Impute observed values below the limit of detection (LOD) via censored likelihood
multiple imputation (CLMI) in single-pollutant models, developed by Boss et al (2019)
<doi:10.1097/EDE.0000000000001052>.
