blandr.draw: Bland-Altman drawing function for R

In blandr: Bland-Altman Method Comparison

Bland-Altman drawing function for R

Description

Bland-Altman drawing function. Depends on the blandr.statistics function in the package. Will generate a plot via the standard R plotting functions.

Usage

blandr.draw(
  method1,
  method2,
  method1name = "Method 1",
  method2name = "Method 2",
  plotTitle = "Bland-Altman plot for comparison of 2 methods",
  sig.level = 0.95,
  LoA.mode = 1,
  annotate = FALSE,
  ciDisplay = TRUE,
  ciShading = TRUE,
  normalLow = FALSE,
  normalHigh = FALSE,
  lowest_y_axis = FALSE,
  highest_y_axis = FALSE,
  point_size = 0.8,
  overlapping = FALSE,
  plotter = "ggplot",
  x.plot.mode = "means",
  y.plot.mode = "difference",
  plotProportionalBias = FALSE,
  plotProportionalBias.se = TRUE,
  assume.differences.are.normal = TRUE
)

Arguments

method1	A vector of numbers corresponding to the results from method 1.
method2	A vector of numbers corresponding to the results from method 2.
method1name	(Optional) Plotting name for 1st method, default 'Method 1'
method2name	(Optional) Plotting name for 2nd method, default 'Method 2'
plotTitle	(Optional) Title name, default 'Bland-Altman plot for comparison of 2 methods'
sig.level	(Optional) Two-tailed significance level. Expressed from 0 to 1. Defaults to 0.95.
LoA.mode	(Optional) Switch to change how accurately the limits of agreement (LoA) are calculated from the bias and its standard deviation. The default is LoA.mode=1 which calculates LoA with the more accurate 1.96x multiplier. LoA.mode=2 uses the 2x multiplier which was used in the original papers. This should really be kept at default, except to double check calculations in older papers.
annotate	(Optional) TRUE/FALSE switch to provides annotations to plot, default=FALSE
ciDisplay	(Optional) TRUE/FALSE switch to plot confidence intervals for bias and limits of agreement, default=TRUE
ciShading	(Optional) TRUE/FALSE switch to plot confidence interval shading to plot, default=TRUE
normalLow	(Optional) If there is a normal range, entering a continuous variable will plot a vertical line on the plot to indicate its lower boundary
normalHigh	(Optional) If there is a normal range, entering a continuous variable will plot a vertical line on the plot to indicate its higher boundary
lowest_y_axis	(Optional) Defaults to NULL If given a continuous variable will use this as the lower boundary of the y axis. Useful if need multiple plots with equivalent y-axes.
highest_y_axis	(Optional) Defaults to NULL If given a continuous variable will use this as the upper boundary of the y axis. Useful if need multiple plots with equivalent y-axes.
point_size	(Optional) Size of marker for each dot. Default is cex=0.8
overlapping	(Optional) TRUE/FALSE switch to increase size of plotted point if multiple values using ggplot's geom_count, default=FALSE. Not currently recommend until I can tweak the graphics to make them better
plotter	(Optional- default='ggplot') Selects which graphics engine to use to plot the Bland-Altman charts. 2 options are 'ggplot' or 'rplot'. If unknown parameter sent, will default to 'ggplot'
x.plot.mode	(Optional) Switch to change x-axis from being plotted by means (="means") or by either 1st method (="method1") or 2nd method (="method2"). Default is "means". Anything other than "means" will switch to default mode.
y.plot.mode	(Optional) Switch to change y-axis from being plotted by difference (="difference") or by proportion magnitude of measurements (="proportion"). Default is "difference". Anything other than "proportional" will switch to default mode.
plotProportionalBias	(Optional) TRUE/FALSE switch. Plots a proportional bias line. Default is FALSE.
plotProportionalBias.se	(Optional) TRUE/FALSE switch. If proportional bias line is drawn, switch to plot standard errors. See stat_smooth for details. Default is TRUE.
assume.differences.are.normal	(Optional, not operationally used currently) Assume the difference of means has a normal distribution. Will be used to build further analyses

Note

Started 2015-11-14

Last update 2015-11-19

Originally designed for LAVAS and CVLA

Author(s)

Deepankar Datta [e-mail]

Examples

# Generates two random measurements
measurement1 <- rnorm(100)
measurement2 <- rnorm(100)

# Generates a plot, with no optional arguments
blandr.draw( measurement1 , measurement2 )

# Generates a plot, using the in-built R graphics
blandr.draw( measurement1 , measurement2 , plotter = 'rplot' )

# Generates a plot, with title changed
blandr.draw( measurement1 , measurement2 , plotTitle = 'Bland-Altman example plot' )

# Generates a plot, with title changed, and confidence intervals off
blandr.draw( measurement1 , measurement2 , plotTitle = 'Bland-Altman example plot' ,
ciDisplay = FALSE , ciShading = FALSE )

blandr documentation built on June 22, 2024, 10:58 a.m.