cpm.train

Training a connectome-based predictive model using a fixed p-value threshold

cpm.train(data, outcome, p = 0.05)

Arguments

data

An N x E matrix containing the vectorized edges; where N = number of subjects, E=number of edges

outcome

The outcome variable to predict

p

The p-value threshold of a Pearson's correlation test between the feature and outcome that determines if the feature is selected. Set to 0.05 by default.

Value

Returns a list object containing

• weights vector of 1s (positive edges), 0s and -1s (negative edges) indicating the selected edges

• pos.network.coef linear regression coefficients of the positive network strength model

• neg.network.coef linear regression coefficients of the negative network strength model

• both.network.coef linear regression coefficients of the positive and negative network strength model

Details

This function implements the connectome-based prediction model described in Shen et al. (2017)

Examples

if (FALSE) { # \dontrun{
model1=cpm.train(data=FC_data,outcome=dat_beh$age, p=0.05)
} # }