Function to compute predicted risks for all individuals in the (new)dataset.
1 
riskModel 
Name of logistic regression model that can be fitted using
the function 
data 
Data frame or matrix that includes the ID number and predictor variables. 
cID 
Column number of ID variable. The ID number and predicted risks
will be saved under 
filename 
Name of the output file in which the ID number and
estimated predicted risks will be saved. The file is saved in the working
directory as a txt file. Example: filename="name.txt". When no 
The function computes predicted risks from a specified logistic regression model.
The function fitLogRegModel
can be used to construct such a model.
The function returns a vector of predicted risks.
fitLogRegModel
, plotCalibration
,
plotROC
, plotPriorPosteriorRisk
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22  # specify dataset with outcome and predictor variables
data(ExampleData)
# specify column number of the outcome variable
cOutcome < 2
# specify column number of ID variable
cID < 1
# specify column numbers of nongenetic predictors
cNonGenPred < c(3:10)
# specify column numbers of nongenetic predictors that are categorical
cNonGenPredCat < c(6:8)
# specify column numbers of genetic predictors
cGenPred < c(11,13:16)
# specify column numbers of genetic predictors that are categorical
cGenPredCat < c(0)
# fit logistic regression model
riskmodel < fitLogRegModel(data=ExampleData, cOutcome=cOutcome,
cNonGenPreds=cNonGenPred, cNonGenPredsCat=cNonGenPredCat,
cGenPreds=cGenPred, cGenPredsCat=cGenPredCat)
# obtain predicted risks
predRisk < predRisk(riskModel=riskmodel)

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