plotEstimates: Plot the results of a network meta-analysis

In RichardBirnie/mautils: Utilities to facilitate an automated workflow for meta-analysis

Description

Plot the results of a network meta-analysis

Usage

plotEstimates(df, yvar, xvar = "median", lowLimit = "CrI_lower",
  hiLimit = "CrI_upper", xlabel = "Effect Estimate", noEffectLine = 1)

Arguments

df	A data frame containing summary statistics for the posterior distribution of the parameters in a network meta-analysis.
yvar	A character string specifying the name of the column in df that contains the variable to be used on the y-axis. Usually this will be the names of the treatments in the network.
xvar	A character string specifying the name of the column in df that contains the variable to be used on the x-axis. Usually this will be the median of the posterior distribution of the treatment effect
lowLimit, hiLimit	Character strings specifying the names of the columns in df that specify the lower and upper limits of the 95% credible intervals. If you have followed the work flow in this package these will be called 'CrI_lower' and 'CrI_upper' respectively.
xlabel	A character string to be used as a label on the x-axis. This is usually the type of effect measure, e.g. 'Odds ratio', 'Rate Ratio' etc.
noEffectLine	An integer indicating where to draw the line of no effect. For ratio measures this is usually 1. For mean differences this is usually 0.
report_order	A character string indicating whether the treatments should be reported in the order the order they were provided (default) or if a custom order is required. Acceptable values are 'default' or 'custom'.

Details

This function should most commonly be used with the output from extractTOI to plot the results for a particular treatment of interest. This function uses ggplot to do the actual plotting and returns a ggplot object which may be further modified if required or just saved to a file.

Value

A ggplot object

See Also

extractTOI, geom_point, geom_errorbarh

RichardBirnie/mautils documentation built on July 12, 2019, 8:56 p.m.