MultipleTables.plot {mmeta} | R Documentation |
Plot Method for Multipletables
objects
Description
Produces a variety of plots for multiple tables analysis
Usage
MultipleTables.plot(
multiple_tables_object,
plot_type = "forest",
layout_type = "overlay",
selected_study_names = NULL,
xlim = NULL,
add_vertical = NULL,
show_CI = TRUE,
by = "line_type"
)
Arguments
multiple_tables_object |
The object inheriting from class |
plot_type |
a character string specifying the kind of plots to
produce. Options are |
layout_type |
a character string specifying the type of the density plots (i.e., when |
selected_study_names |
a numeric value or vector specifying which studies to
be plotted. By default (when |
xlim |
a numeric value specifying the lower and upper limits of the x-axis. Default is NULL.
For forest plots, if the lower bound of any measure is smaller than |
add_vertical |
a numeric value specifying the x-value for a vertical
reference line at |
show_CI |
a logical value; If TRUE (default) the forest plot will show the lower & upper bounds of CIs,
else the the lower & upper bounds of CIs will be omitted. This argument is always NULL when |
by |
a character string specifying the way to distinguish different plots. Options are |
Details
If plot_type=‘density’
and layout_type='sidebyside'
, the posterior distributions of all
study-specific measure are displayed side by side in 4-panel plots with study names.
If plot_type=‘density’
and layout_type='overlap'
, the posterior distributions of all
study-specific measure are displayed in one graph. To clarity, it
is advisable to specify a few studies by selected_study_names
argument.
If type='forest')
and layout_type='NULL'
, a forest plot of all study-specific and
overall measure with 95% credible/confidence intervals are plotted.
Value
A ggplot2 object is returned.
See Also
MultipleTables.create
, MultipleTables.modelFit
, and MultipleTables.summary
.
Examples
library(mmeta)
library(ggplot2)
## Analyze the dataset colorectal to conduct exact inference of the odds ratios
data(colorectal)
colorectal['study_name'] <- colorectal['studynames']
## If exact method is used, the codes for sampling method are similar.
## Create object multiple_tables_obj_exact
multiple_tables_obj_exact <- MultipleTables.create(data=colorectal,
measure='OR', model= 'Sarmanov')
## Model fit default
multiple_tables_obj_exact <- MultipleTables.modelFit(multiple_tables_obj_exact, method = 'exact')
## Summary of the fitting process (default)
multiple_tables_obj_exact <- MultipleTables.summary(multiple_tables_obj_exact)
## Density plot, overlay
## Note: There are no enough types of line, if we have too many densities!
MultipleTables.plot(multiple_tables_obj_exact, plot_type = 'density',
layout_type = 'overlay')
## Choose Set by = ‘color’
MultipleTables.plot(multiple_tables_obj_exact, plot_type = 'density',
layout_type = 'overlay',by = 'color')
## Set by = ‘color’ and specify xlim as 0 to 5.
MultipleTables.plot(multiple_tables_obj_exact, plot_type = 'density',
layout_type = 'overlay', by = 'color', xlim = c(0,5))
## Set by = ‘color’ and specify xlim as 0 to 5 and add vertical line at OR = 1
MultipleTables.plot(multiple_tables_obj_exact, plot_type = 'density',
layout_type = 'overlay', by = 'color',xlim = c(0,5), add_vertical = 1)
## If select three studies
MultipleTables.plot(multiple_tables_obj_exact, plot_type = 'density',
layout_type = 'overlay',selected_study_names = c('Bell','Chen','Oda'), xlim = c(0,5))
## We can add external layouts for the return ggplot2. xlab as Odds ratio
ggplot2_obj <- MultipleTables.plot(multiple_tables_obj_exact,
plot_type = 'density', layout_type = 'overlay', by = 'color',xlim = c(0,5))
ggplot2_obj + xlab('Odds Ratio') + ggtitle('OR ration for XX cancer')
## density plot, plot side by side
MultipleTables.plot(multiple_tables_obj_exact, plot_type = 'density',
layout_type = 'side_by_side')
## Forest plot (default)
MultipleTables.plot(multiple_tables_obj_exact, plot_type = 'forest')
## forest plot: not show the CIs
MultipleTables.plot(multiple_tables_obj_exact, plot_type = 'forest',
add_vertical = 1, show_CI = FALSE)