Estimating the proportion of MCAR values in a sample using a probit model.

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Description

This function allows estimating the proportion of MCAR values in a sample using a probit model.

Usage

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Arguments

tab

A data matrix containing numeric and missing values. Each column of this matrix is assumed to correspond to an experimental sample, and each row to an identified peptide.

conditions

A vector of factors indicating the biological condition to which each column (experimental sample) belongs.

Value

A list composed of:

pi.mcar

The estimated proportion of MCAR values.

coef1

The estimated intercept of each probit model estimated in a sample.

coef2

The estimated coefficient of each probit model estimated in a sample.

Author(s)

Quentin Giai Gianetto <quentin2g@yahoo.fr>

See Also

estim.mix

Examples

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#Simulating data
res.sim=sim.data(nb.pept=2000,nb.miss=600,pi.mcar=0.2,para=10,nb.cond=2,nb.repbio=3,
nb.sample=5,m.c=25,sd.c=2,sd.rb=0.5,sd.r=0.2);

#Deleting rows without any observed value in a condition
result=delete.na.rows(tab=res.sim$dat.obs, tab.c=res.sim$dat.comp, conditions=res.sim$condition,
list.MCAR=res.sim$list.MCAR);

#Proportion of MCAR values in each sample
pi.mcar.probit(tab=result$tab.mod, conditions=res.sim$condition);

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