# Function to plot histogram of risks separated for individuals with and without the outcome of interest. ```r plotRiskDistribution(data, cOutcome, risks, interval, rangexaxis, rangeyaxis, plottitle, xlabel, ylabel, labels, fileplot, plottype) ``` ## Returns The function creates the histogram of risks separated for individuals with and without the outcome of interest. ## See Also `plotROC`, `riskScore` ## Arguments - `data`: Data frame or numeric matrix that includes the outcome and predictor variables. - `cOutcome`: Column number of the outcome variable. - `risks`: Risk of each individual. It is specified by either a vector of risk scores or a vector of predicted risks. - `interval`: Size of the risk intervals. For example, `interval=.1` will construct the following intervals for predicted risks: `0-0.1, 0.1-0.2,..., 0.9-1`. - `rangexaxis`: Range of the x-axis. Specification of `rangexaxis` is optional. - `rangeyaxis`: Range of the y-axis. - `plottitle`: Title of the plot. Specification of `plottitle` is optional. Default is "Histogram of risks". - `xlabel`: Label of x-axis. Specification of `xlabel` is optional. Default is "Risk score". - `ylabel`: Label of y-axis. Specification of `ylabel` is optional. Default is "Percentage". - `labels`: Labels given to the groups of individuals without and with the outcome of interest. Specification of `labels` is optional. Default is `c("Without outcome", "With outcome")`. - `fileplot`: Name of the output file that contains the plot. The file is saved in the working directory in the format specified under `plottype`. Example: `fileplot="plotname"`. Note that the extension is not specified here. When `fileplot` is not specified, the plot is not saved. - `plottype`: The format in which the plot is saved. Available formats are wmf, emf, png, jpg, jpeg, bmp, tif, tiff, ps, eps or pdf. For example, `plottype="eps"` will save the plot in eps format. When `plottype` is not specified, the plot will be saved in jpg format. ## Examples ```r # specify dataset with outcome and predictor variables data(ExampleData) # specify column number of the outcome variable cOutcome <- 2 # fit a logistic regression model # all steps needed to construct a logistic regression model are written in a function # called 'ExampleModels', which is described on page 4-5 riskmodel <- ExampleModels()$riskModel2 # obtain predicted risks predRisk <- predRisk(riskmodel) # specify the size of each interval interval <- .05 # specify label of x-axis xlabel <- "Predicted risk" # specify label of y-axis ylabel <- "Percentage" # specify range of x-axis xrange <- c(0,1) # specify range of y-axis yrange <- c(0,40) # specify title for the plot maintitle <- "Distribution of predicted risks" # specify labels labels <- c("Without outcome", "With outcome") # produce risk distribution plot plotRiskDistribution(data=ExampleData, cOutcome=cOutcome, risks=predRisk, interval=interval, plottitle=maintitle, rangexaxis=xrange, rangeyaxis=yrange, xlabel=xlabel, ylabel=ylabel, labels=labels) ```

plotRiskDistribution function