2nd Rubin's rule Between-Imputation component (all peptides)

Computes the between-imputation component in the 2nd Rubin's rule for all peptides.

rubin2bt.all(
  data,
  funcmean = meanImp_emmeans,
  metacond,
  is.parallel = FALSE,
  verbose = FALSE
)

Arguments

data

dataset

funcmean

function that should be used to compute the mean

metacond

a factor to specify the groups

is.parallel

should parallel computing be used?

verbose

should messages be displayed?

Value

List of variance-covariance matrices.

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. doi:10.1371/journal.pcbi.1010420 .

Author

Frédéric Bertrand

Examples

library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], conditions = 
attr(datasim,"metadata")$Condition, method = "MLE")
rubin2bt.all(datasim_imp[1:5,,],funcmean = meanImp_emmeans,
attr(datasim,"metadata")$Condition)
#> [[1]]
#>      [,1] [,2]
#> [1,]    0    0
#> [2,]    0    0
#> 
#> [[2]]
#>      [,1] [,2]
#> [1,]    0    0
#> [2,]    0    0
#> 
#> [[3]]
#>      [,1] [,2]
#> [1,]    0    0
#> [2,]    0    0
#> 
#> [[4]]
#>      [,1] [,2]
#> [1,]    0    0
#> [2,]    0    0
#> 
#> [[5]]
#>      [,1] [,2]
#> [1,]    0    0
#> [2,]    0    0
#>