Computes the first Rubin's rule for a given peptide.
Usage
rubin1.one(peptide, data, funcmean = meanImp_emmeans, 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 vector of estimated parameters.
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.
Examples
library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], conditions =
attr(datasim,"metadata")$Condition, method = "MLE")
rubin1.one(1,datasim_imp,funcmean = meanImp_emmeans,
attr(datasim,"metadata")$Condition)
#> [1] 99.02599 200.23868
