Analysis with Missing Data

clikcorr

  • A profile likelihood based method of estimation and inference on the correlation coefficient of bivariate data with different types of censoring and missingness.
  • Faculty: Yanming Li.  Download: CRAN.

IVEware

  • 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.
  • Faculty: Trivellore Raghunathan, Roderick Little, Michael Elliott. Download: Website.

Lodi

  • 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>.
  • Faculty: Seunggeun Shawn Lee, Bhramar Mukherjee, Min Zhang. Download: CRAN.
  • References: Boss, J., Mukherjee, B., Ferguson, K.K., Aker, A., Alshawabkeh, A.N., Cordero, J.F., Meeker, J.D. and Kim, S., 2019. Estimating outcome-exposure associations when exposure biomarker detection limits vary across batches. Epidemiology, 30(5), pp.746-755.