PReMiuM (version 3.0.24)

plotPredictions: Plot the conditional density using the predicted scenarios

Description

Plots the conditional density for the predicted scenarios provided. It produces a pdf with a page for each predictive scenario provided. Each page has a plot of the

Usage

plotPredictions(outfile, runInfoObj, predictions,
    logOR=FALSE)

Arguments

outfile

String. The name of the output PDF file. The default is "condDensity.pdf".

runInfoObj

An object of type runInfoObj which contains all the details about the run of profRegr.

predictions

An object of type predictions which contains all the details about the run of calcPredictions.

logOR

Whether to plot the response probability or log odds ratios. The default is FALSE and the response probability is plotted.

Value

• The output is a plot in PDF format.

Authors

Silvia Liverani, Department of Epidemiology and Biostatistics, Imperial College London and MRC Biostatistics Unit, Cambridge, UK

Maintainer: Silvia Liverani

References

Liverani, S., Hastie, D. I., Azizi, L., Papathomas, M. and Richardson, S. (2013) PReMiuM: An R package for Profile Regression Mixture Models using Dirichlet Processes. Submitted. Available at http://uk.arxiv.org/abs/1303.2836

Examples

# example with Bernoulli outcome and Discrete covariates
inputs <- generateSampleDataFile(clusSummaryBernoulliDiscrete())
# prediction profiles
preds<-data.frame(matrix(c(
2, 2, 2, 2, 2,
0, 0, NA, 0, 0),ncol=5,byrow=TRUE))

colnames(preds)<-names(inputs$inputData)[2:(inputs$nCovariates+1)]
# run profile regression
runInfoObj<-profRegr(yModel=inputs$yModel, xModel=inputs$xModel, 
 nSweeps=10000, nBurn=10000, data=inputs$inputData, output="output", 
 covNames=inputs$covNames,predict=preds,
 fixedEffectsNames = inputs$fixedEffectNames)        
dissimObj <- calcDissimilarityMatrix(runInfoObj)
clusObj <- calcOptimalClustering(dissimObj)
riskProfileObj <- calcAvgRiskAndProfile(clusObj)
predictions <- calcPredictions(riskProfileObj,fullSweepPredictions=TRUE,fullSweepLogOR=TRUE)

plotPredictions(outfile="predictiveDensity.pdf",runInfoObj=runInfoObj,
 predictions=predictions,logOR=TRUE)