Plot fitted values from MBNMA model

Plot fitted values from MBNMA model

fitplot(
  mbnma,
  disp.obs = TRUE,
  n.iter = mbnma$BUGSoutput$n.iter,
  n.thin = mbnma$BUGSoutput$n.thin,
  ...
)

Arguments

mbnma

An S3 object of class "mbnma" generated by running a dose-response MBNMA model

disp.obs

A boolean object to indicate whether raw data responses should be plotted as points on the graph

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_line()

Value

Generates a plot of fitted values from the MBNMA model and returns a list containing the plot (as an object of class(c("gg", "ggplot"))), and a data.frame of posterior mean fitted values for each observation.

Details

Fitted values should only be plotted for models that have converged successfully. If fitted values (theta) have not been monitored in mbnma$parameters.to.save then additional iterations will have to be run to get results for these.

Examples

# \donttest{
# Using the triptans data
network <- mbnma.network(triptans)
#> Values for `agent` with dose = 0 have been recoded to `Placebo`
#> agent is being recoded to enforce sequential numbering

# Run an Emax dose-response MBNMA and predict responses
emax <- mbnma.run(network, fun=demax(), method="random")
#> `likelihood` not given by user - set to `binomial` based on data provided
#> `link` not given by user - set to `logit` based on assigned value for `likelihood`
#> Compiling model graph
#>    Resolving undeclared variables
#>    Allocating nodes
#> Graph information:
#>    Observed stochastic nodes: 182
#>    Unobserved stochastic nodes: 197
#>    Total graph size: 4115
#> 
#> Initializing model
#> 

# Plot fitted values and observed values
fitplot(emax)
#> `theta` not monitored in mbnma$parameters.to.save.
#> additional iterations will be run in order to obtain results


# Plot fitted values only
fitplot(emax, disp.obs=FALSE)
#> `theta` not monitored in mbnma$parameters.to.save.
#> additional iterations will be run in order to obtain results


# A data frame of fitted values can be obtained from the object
#returned by `fitplot`
fits <- fitplot(emax)
#> `theta` not monitored in mbnma$parameters.to.save.
#> additional iterations will be run in order to obtain results

head(fits$fv)
#>     study arm       mean       facet fupdose groupvar studyID          y
#> 711     1   2 -2.0657641 sumatriptan     0.0        1      27         NA
#> 71      1   2 -0.8904337 sumatriptan     0.5        1      27 -0.7845814
#> 141     1   3 -0.8547510 sumatriptan     1.0        1      37 -0.9614112
#> 211     1   4 -0.5605191 sumatriptan     2.0        1      66 -0.7429087
#> 721     2   2 -2.0657641  eletriptan     0.0        2      27         NA
#> 72      2   2 -0.7440639  eletriptan     1.0        2      27 -0.7522361
# }