timeplot: Plot raw responses over time by treatment or class

In MBNMAtime: Run Time-Course Model-Based Network Meta-Analysis (MBNMA) Models

Plot raw responses over time by treatment or class

Description

Plot raw responses over time by treatment or class

Usage

timeplot(network, level = "treatment", plotby = "arm", link = "identity", ...)

Arguments

network	An object of class "mb.network".
level	A string indicating whether nodes/facets should represent treatment or class in the plot. Can be used to examine the expected impact of modelling class/agent effects.
plotby	A character object that can take either "arm" to indicate that raw responses should be plotted separately for each study arm, or "rel" to indicate that the within-study relative effects/treatment differences should be plotted. In this way the time-course of both the absolute effects and the relative effects can be examined.
link	Can take either "identity" (the default), "log" (for modelling Ratios of Means \insertCitefriedrich2011MBNMAtime) or "smd" (for modelling Standardised Mean Differences - although this also corresponds to an identity link function).
...	Arguments to be sent to ggplot()

Details

Plots can be faceted by either treatment (level="treatment") or class (level="class") to investigate similarity of treatment responses within classes/agents. Points represent observed responses and lines connect between observations within the same study and arm.

Value

The function returns an object of ⁠class(c("gg", "ggplot")⁠. Characteristics of the object can therefore be amended as with other plots generated by ggplot().

Examples

# Make network
goutnet <- mb.network(goutSUA_CFB)

# Use timeplot to plot responses grouped by treatment
timeplot(goutnet)

# Use timeplot ot plot resposes grouped by class
timeplot(goutnet, level="class")

# Plot matrix of relative effects
timeplot(goutnet, level="class", plotby="rel")

# Plot using Standardised Mean Differences
copdnet <- mb.network(copd)
timeplot(copdnet, plotby="rel", link="smd")

MBNMAtime documentation built on Oct. 14, 2023, 5:08 p.m.