Description Usage Arguments Note Author(s) Examples

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

1 2 3 4 5 6 7 8 9 | ```
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)
``` |

`method1` |
A list of numbers. |

`method2` |
A list of numbers. |

`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, deafault=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 |

Started 2015-11-14

Last update 2015-11-19

Originally designed for LAVAS and CVLA

Deepankar Datta <[email protected]>

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
# 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 )
``` |

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