Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics
Fig 2
(1) Initial dataset with missing values. It is supposed to have N observations that are split into K groups. (2) Multiple imputation provides D estimators for the vector of parameters of interest. (3a) The D estimators are combined using the first Rubin’s rule to get the combined estimator. (3b) The estimator of the variance-covariance matrix of the combined estimator is provided by the second Rubin’s rule.