within_variance_comp_emmeans: Multiple Imputation Within Variance Component

In mariechion/mi4p: Multiple Imputation for Proteomics

Multiple Imputation Within Variance Component

Description

Computes the multiple imputation within variance component using the emmeans package.

Usage

within_variance_comp_emmeans(ind, peptide, data, metacond)

Arguments

ind	index
peptide	name of the peptide
data	dataset
metacond	a factor to specify the groups

Value

A variance-covariance matrix.

Author(s)

Frédéric Bertrand

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. \Sexpr[results=rd]{tools:::Rd_expr_doi("doi:10.1371/journal.pcbi.1010420")}.

Examples

library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], conditions = 
attr(datasim,"metadata")$Condition, method = "MLE")
within_variance_comp_emmeans(1,1,datasim_imp,
attr(datasim,"metadata")$Condition)

mariechion/mi4p documentation built on Oct. 3, 2024, 4:50 a.m.