Adds sections of JAGS code for an MBNMA model that correspond to the likelihood

Usage

write.likelihood(
  model,
  timecourse,
  rho = 0,
  covar = "varadj",
  link = "identity",
  sdscale = FALSE,
  fun
)

Arguments

model

A character object of JAGS MBNMA model code

timecourse

A character object representing the time-course used in the MBNMA model

rho

The correlation coefficient when modelling within-study correlation between time points. The default is a string representing a prior distribution in JAGS, indicating that it be estimated from the data (e.g. rho="dunif(0,1)"). rho also be assigned a numeric value (e.g. rho=0.7), which fixes rho in the model to this value (e.g. for use in a deterministic sensitivity analysis). If set to rho=0 (the default) then this implies modelling no correlation between time points.

covar

A character specifying the covariance structure to use for modelling within-study correlation between time-points. This can be done by specifying one of the following:

"varadj" - a univariate likelihood with a variance adjustment to assume a constant correlation between subsequent time points (Jansen et al. 2015) . This is the default.
"CS" - a multivariate normal likelihood with a compound symmetry structure
"AR1" - a multivariate normal likelihood with an autoregressive AR1 structure

link

Can take either "identity" (the default), "log" (for modelling Ratios of Means (Friedrich et al. 2011) ) or "smd" (for modelling Standardised Mean Differences - although this also corresponds to an identity link function).

sdscale

Logical object to indicate whether to write a model that specifies a reference SD for standardising when modelling using Standardised Mean Differences. Specifying sdscale=TRUE will therefore only modify the model if link function is set to SMD (link="smd").

fun

An object of class "timefun" generated (see Details) using any of tloglin(), tpoly(), titp(), temax(), tfpoly(), tspline() or tuser()

Value

A character vector of JAGS MBNMA model code that includes likelihood components of the model