Plot deviance contributions from an MBNMA model
devplot( mbnma, plot.type = "box", facet = TRUE, dev.type = "resdev", n.iter = mbnma$BUGSoutput$n.iter/2, n.thin = mbnma$BUGSoutput$n.thin, ... )
mbnma: An S3 object of class "mbnma" generated by running a dose-response MBNMA model
plot.type: Deviances can be plotted either as scatter points ("scatter") or as boxplots ("box")
facet: A boolean object that indicates whether or not to facet (by agent for MBNMAdose
and by treatment for MBNMAtime)
dev.type: STILL IN DEVELOPMENT FOR MBNMAdose! Deviances to plot - can be either residual deviances ("resdev", the default) or deviances ("dev")
n.iter: number of total iterations per chain (including burn in; default: 2000)
n.thin: thinning rate. Must be a positive integer. Set n.thin > 1 to save memory and computation time if n.iter is large. Default is max(1, floor(n.chains * (n.iter-n.burnin) / 1000)) which will only thin if there are at least 2000 simulations.
...: Arguments to be sent to ggplot2::geom_point() or ggplot2::geom_boxplot
Generates a plot of deviance contributions and returns a list containing the plot (as an object of class(c("gg", "ggplot"))), and a data.frame of posterior mean deviance/residual deviance contributions for each observation.
Deviances should only be plotted for models that have converged successfully. If deviance contributions have not been monitored in mbnma$parameters.to.save then additional iterations will have to be run to get results for these.
For MBNMAtime, deviance contributions cannot be calculated for models with a multivariate likelihood (i.e. those that account for correlation between observations) because the covariance matrix in these models is treated as unknown (if rho = "estimate") and deviance contributions will be correlated.
# Using the triptans data network <- mbnma.network(triptans) # Run an Emax dose-response MBNMA and predict responses emax <- mbnma.run(network, fun=demax(), method="random") # Plot deviances devplot(emax) # Plot deviances using boxplots devplot(emax, plot.type="box") # Plot deviances on a single scatter plot (not facetted by agent) devplot(emax, facet=FALSE, plot.type="scatter") # A data frame of deviance contributions can be obtained from the object #returned by `devplot` devs <- devplot(emax) head(devs$dev.data) # Other deviance contributions not currently implemented but in future #it will be possible to plot them like so #devplot(emax, dev.type="dev")