Description Usage Arguments Details Value References Examples

Modified Bland-Altman plot for multiple raters

1 2 3 4 |

`rater` |
Variable indicating which rater made the rating. |

`subject` |
Variable for the subject. |

`variable` |
Variable containing the ratings of the subjects. |

`data` |
The dataframe |

`LoA` |
The limits of agreement that have to be used. See Details. |

`ArgzLoess` |
Arguments for |

`symbols.graph` |
Optional, the symbols to be used in the graph for the raters. |

`colSymbols` |
Optional, the color of the symbols |

`Legend` |
Logical, indicates whether a legend has to be printed. Default is |

`ArgzLegend` |
The arguments for the legend, see |

`xlab` |
The label for the x-axis. |

`ylab` |
The label for the y-axis. |

`...` |
Additional arguments to be passed to |

The limits of agreement (LoA) have to be interpreted differently than in Bland-Altman plots with 2 raters. In the modified Bland-Altman
plots, the LoA indicate how different an individual rater can be when compared with the mean of all the raters (Jones et al., 2011). However, as with the
Bland-Altman plots for 2 raters, it may be that the variability of the differences increase as the magnitude of the measurement increases (Bland and
Altman, 1999). Alternative LoA can then be plotted using a method based on the method of Royston and Wright (1998). Specifying `LoA="loess"`

, we get
approximate 2.5 and 97.5 percentile curves. In this method, the standard deviation of the difference scores per subject is calculated and the LoA
per subject are calculated as -/+ 1.96 times the standard deviation. A loess fit is then used to connect these LoA per subject. Note that we assume
that the difference scores are normally distributed (with mean 0 as we are working with centered values).

Returns a list with the following objects

`AnovaSummary` |
The summary of the two-way ANOVA |

`AvgPerSubject` |
The average score per subject. |

`LoA` |
The limits of agreement calculated according to Jones et al. (2011). |

`ICC` |
The intraclass correlation coefficients. See |

Bland, J.M., Altman, D.G.(1999). Measuring agreement in method comparison studies. *Statistical Methods In Medical Research*,
Vol.8(2), pp. 135-160

Jones, M., Dobson, A., O'Brian, S. (2011). A graphical method for assessing agreement with the
mean between multiple observers using continuous measures. *Int J Epidemiol*. Vol.40: pp. 1308-1313.

Royston, P., Wright, E.M. (1988). How to construct 'normal ranges' for fetal variables. *Ultrasound Obstet Gynecol*, Vol.11: pp. 30-38.

1 2 | ```
data(DentalStudy)
BAplotMultipleR(dentist, patient, DMFS, DentalStudy)
``` |

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