Estimating the proportion of MCAR values in a sample using a logit model.
This function allows estimating the proportion of MCAR values in a sample using a logit model.
pi.mcar.logit(tab,conditions)
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. |
A list composed of:
pi.mcar |
The estimated proportion of MCAR values. |
coef1 |
The estimated intercept of each logit model estimated in a sample. |
coef2 |
The estimated coefficient of each logit model estimated in a sample. |
Quentin Giai Gianetto <quentin2g@yahoo.fr>
#Simulating data res.sim=sim.data(nb.pept=2000,nb.miss=600); #Proportion of MCAR values in each sample pi.mcar.logit(tab=res.sim$dat.obs,conditions=res.sim$conditions)
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