Bland-Altman Change plot
BAC_plot( data, cols = names(data), reliability = NULL, pointSize = 2, deterioratedColor = "#482576E6", unchangedColor = "#25848E80", improvedColor = "#7AD151E6", zeroLineColor = "black", zeroLineType = "dashed", ciLineColor = "red", ciLineType = "solid", conf.level = 0.95, theme = ggplot2::theme_minimal(), ignoreBias = FALSE, iccFromPsych = FALSE, iccFromPsychArgs = NULL )
The data frame; if it only has two columns, the first of
which is the pre-change column,
cols can be left empty.
The names of the columns with the data; the first is the column with the pre-change data, the second the column after the change.
The reliability estimate, for example as obtained with
ICC() function in the
psych() package; can be omitted, in which
case the intraclass correlation is computed.
The size of the points in the plot.
The colors to use for cases who deteriorate, stay the same, and improve, respectively.
The colors for the line at 0 (no change) and at the confidence interval bounds (i.e. the point at which a difference becomes indicative of change given the reliability), respectively.
The line types for the line at 0 (no change) and at the confidence interval bounds (i.e. the point at which a difference becomes indicative of change given the reliability), respectively.
The confidence level of the confidence interval.
The ggplot2 theme to use.
Whether to ignore bias (i.e. allow the measurements at
the second time to shift upwards or downwards). If
FALSE, the variance
associated with such a shift is considered error variance (i.e.
Whether to compute ICC using the
If using the
psych::ICC() function, the arguments
A ggplot2 plot.