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It creates a scatter plot of the difference between observed and predicted values (obs-pred) vs. observed values.

Usage

bland_altman_plot(
  data = NULL,
  obs,
  pred,
  shape_type = NULL,
  shape_size = NULL,
  shape_color = NULL,
  shape_fill = NULL,
  zeroline_type = NULL,
  zeroline_size = NULL,
  zeroline_color = NULL,
  limitsline_type = NULL,
  limitsline_size = NULL,
  limitsline_color = NULL,
  na.rm = TRUE
)

Arguments

data

(Optional) argument to call an existing data frame containing the data.

obs

Vector with observed values (numeric).

pred

Vector with predicted values (numeric).

shape_type

number indicating the shape type for the data points.

shape_size

number indicating the shape size for the data points.

shape_color

string indicating the shape color for the data points.

shape_fill

string indicating the shape fill for the data points.

zeroline_type

string or integer indicating the zero line-type.

zeroline_size

number indicating the zero line size.

zeroline_color

string indicating the zero line color.

limitsline_type

string or integer indicating the limits (+/- 1.96*SD) line-type.

limitsline_size

number indicating the limits (+/- 1.96*SD) line size.

limitsline_color

string indicating the limits (+/- 1.96*SD) line color.

na.rm

Logic argument to remove rows with missing values

Value

an object of class ggplot.

Details

For more details, see online-documentation

References

Bland & Altman (1986). Statistical methods for assessing agreement between two methods of clinical measurement The Lancet 327(8476), 307-310 doi:10.1016/S0140-6736(86)90837-8

See also

Examples

# \donttest{
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- rnorm(n = 100, mean = 0, sd = 10)
bland_altman_plot(obs = X, pred = Y)

# }