Synthesise single arm dose = 0 / placebo studies to estimate E0

Synthesises single arm studies to estimate E0. Used in predicting responses from a dose-response MBNMA.

ref.synth(
  data.ab,
  mbnma,
  synth = "fixed",
  n.iter = mbnma$BUGSoutput$n.iter,
  n.burnin = mbnma$BUGSoutput$n.burnin,
  n.thin = mbnma$BUGSoutput$n.thin,
  n.chains = mbnma$BUGSoutput$n.chains,
  ...
)

Arguments

data.ab

A data frame of arm-level data in "long" format containing the columns:

  • studyID Study identifiers

  • y Numeric data indicating the aggregate response for a continuous outcome. Required for continuous data.

  • se Numeric data indicating the standard error for a given observation. Required for continuous data.

  • r Numeric data indicating the number of responders within a study arm. Required for binomial or poisson data.

  • n Numeric data indicating the total number of participants within a study arm. Required for binomial data

  • E Numeric data indicating the total exposure time for participants within a study arm. Required for poisson data.

mbnma

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

synth

A character object that can take the value "fixed" or "random" to specify the the type of pooling to use for synthesis of E0 if a data frame has been provided for it. Using "random" rather than "fixed" for synth will result in wider 95\% CrI for predictions.

n.iter

number of total iterations per chain (including burn in; default: 2000)

n.burnin

length of burn in, i.e. number of iterations to discard at the beginning. Default is n.iter/2, that is, discarding the first half of the simulations. If n.burnin is 0, jags() will run 100 iterations for adaption.

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.

n.chains

number of Markov chains (default: 3)

...

Arguments to be sent to R2jags::jags() for synthesis of the network reference treatment effect (using ref.synth())

Value

A list of named elements corresponding to E0 and the between-study standard deviation for E0 if synth="random". Each element contains the full MCMC results from the synthesis.

Details

data.ab can be a collection of studies that closely resemble the population of interest intended for the prediction, which could be different to those used to estimate the MBNMA model, and could include single arms of RCTs or observational studies. If other data is not available, the data used to estimate the MBNMA model can be used by selecting only the studies and arms that investigate dose = 0 (placebo).

Defaults for n.iter, n.burnin, n.thin and n.chains are those used to estimate mbnma.

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
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
#> 

# Data frame for synthesis can be taken from placebo arms
ref.df <- triptans[triptans$agent=="placebo",]

# Meta-analyse placebo studies using fixed treatment effects
E0 <- ref.synth(ref.df, emax, synth="fixed")
#> [1] "Data frame must contain only data from reference treatment"
#> Values for `agent` with dose = 0 have been recoded to `Placebo`
#> agent is being recoded to enforce sequential numbering
#> Compiling model graph
#>    Resolving undeclared variables
#>    Allocating nodes
#> Graph information:
#>    Observed stochastic nodes: 66
#>    Unobserved stochastic nodes: 1
#>    Total graph size: 1066
#> 
#> Initializing model
#> 
names(E0)
#> [1] "jagsmod" "m.mu"   

# Meta-analyse placebo studies using random treatment effects
E0 <- ref.synth(ref.df, emax, synth="random")
#> [1] "Data frame must contain only data from reference treatment"
#> Values for `agent` with dose = 0 have been recoded to `Placebo`
#> agent is being recoded to enforce sequential numbering
#> Compiling model graph
#>    Resolving undeclared variables
#>    Allocating nodes
#> Graph information:
#>    Observed stochastic nodes: 66
#>    Unobserved stochastic nodes: 68
#>    Total graph size: 1222
#> 
#> Initializing model
#> 
names(E0)
#> [1] "jagsmod" "m.mu"    "sd.mu"  
# }