plotdata function

Basic function to plot the data of meta-analysis of diagnostic test

This function plots the true positive rates vs the false positive rates of each study included in the meta-analysis. Study results are displayed by circles, the diameter of each circle is proportional to the sample size of the study (or table). If subgroups are displayed each group is represented by different colours. This function use the package ggplot2.

plotdata(
  data,
  two.by.two = FALSE,
  group = NULL,
  x.lo = 0,
  x.up = 1,
  y.lo = 0,
  y.up = 1,
  alpha.p = 0.7,
  max.size = 15
)

Arguments

• data: Either a data frame with at least 4 columns containing the true positives (tp), number of patients with disease (n1), false positives (fp), number of patients without disease (n2), or for two.by.two = TRUE a data frame where each line contains the diagnostic results as a two by two table, where the column names are: TP, FP, TN, FN.
• two.by.two: If TRUE indicates that the diagnostic results are given as: TP, FP, TN, FN.
• group: a variable name indicating a group factor
• x.lo: lower limit of the x-axis
• x.up: upper limit of the x-axis
• y.lo: lower limit of the y-axis
• y.up: upper limit of the y-axis
• alpha.p: transparency of the points
• max.size: scale parameter of the maximum size

Examples

## execute analysis
## Not run:

data(ct)
ct$design <- with(ct, factor(design,
             labels = c("Prospective", "Retrospective")))

plotdata(ct,              # Data frame
        group = "design", # Groupping variable
        y.lo = 0.75,      # Lower limit of y-axis
        x.up = 0.75,      # Upper limit of x-axis
        alpha.p = 0.5,    # Transparency of the balls
        max.size = 5)     # Scale the circles
## End(Not run)