# R/blandr.plot.normality.r In blandr: Bland-Altman Method Comparison

```#' @title Bland-Altman histogram and density plot
#'
#' @description Generates  a combined histogram and density curve for Bland-Altman differences
#'
#' @author Deepankar Datta <[email protected]>
#'
#' @param statistics.results A list of statistics generated by the blandr.statistics function: see the function's return list to see what variables are passed to this function
#'
#' @include blandr.statistics.r
#'
#' @export

blandr.plot.normality <- function( statistics.results ) {

# We could do a histogram and density plot by the following
# hist( statistics.results\$differences )
# plot( density( statistics.results\$differences ) )
# qqnorm( results\$differences )
# qqline( results\$differences, col = 2 )
# However ggplot2 is so much more customisable

# ggplot can't use lists, so need to convert the results to a dataframe
results <- data.frame( statistics.results\$differences )
# and rename
names(results)[1] <- "differences"

# Note that having ..density.. below results in a CRAN note
# NULLing it first to handle it -> is a bit hacky but works
# See: https://stackoverflow.com/questions/9439256/how-can-i-handle-r-cmd-check-no-visible-binding-for-global-variable-notes-when#12429344
..density.. <- NULL

# Create the histogram
normality.plot <- ggplot( results , aes( x = results\$differences ) ) +
geom_histogram( aes(y=..density..) , colour="black", fill="white" ) +
geom_density( colour="red" ) +
ylab( "Density" ) +
xlab( "Differences") +
ggtitle("Histogram and density plot of differences")

return(normality.plot)

# END OF FUNCTION
}
```

## Try the blandr package in your browser

Any scripts or data that you put into this service are public.

blandr documentation built on May 2, 2019, 6:50 a.m.