2nd Rubin's rule Between-Imputation Component (a given peptide)

Computes the between-imputation component in the 2nd Rubin's rule for a given peptide.

rubin2bt.one(peptide, data, funcmean, metacond)

Arguments

peptide	peptide for which the variance-covariance matrix should be derived.
data	dataset
funcmean	function that should be used to compute the mean
metacond	a factor to specify the groups

Value

A variance-covariance matrix.

References

M. Chion, Ch. Carapito and F. Bertrand (2021). Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics. arxiv:2108.07086. https://arxiv.org/abs/2108.07086.

Author

Frédéric Bertrand

Examples

library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], conditions = 
attr(datasim,"metadata")$Condition, method = "MLE")
rubin2bt.one(1,datasim_imp,funcmean = meanImp_emmeans,
attr(datasim,"metadata")$Condition)
#>      [,1] [,2]
#> [1,]    0    0
#> [2,]    0    0