prepare_nodesplit {rnmamod}

WinBUGS code for the node-splitting approach

Description

The WinBUGS code, as written by Dias et al. (2010) to run a one-stage Bayesian node-splitting model, extended to incorporate the pattern-mixture model for binary or continuous missing participant outcome data (Spineli et al., 2021; Spineli, 2019).

Usage

prepare_nodesplit(measure, model, assumption)

Arguments

measure

Character string indicating the effect measure. For a binary outcome, the following can be considered: "OR", "RR" or "RD" for the odds ratio, relative risk, and risk difference, respectively. For a continuous outcome, the following can be considered: "MD", "SMD", or "ROM" for mean difference, standardised mean difference and ratio of means, respectively.

model

Character string indicating the analysis model with values "RE", or "FE" for the random-effects and fixed-effect model, respectively. The default argument is "RE".

assumption

Character string indicating the structure of the informative missingness parameter. Set assumption equal to one of the following: "HIE-COMMON", "HIE-TRIAL", "HIE-ARM", "IDE-COMMON", "IDE-TRIAL", "IDE-ARM", "IND-CORR", or "IND-UNCORR". The default argument is "IDE-ARM". The abbreviations "IDE", "HIE", and "IND" stand for identical, hierarchical and independent, respectively. "CORR" and "UNCORR" stand for correlated and uncorrelated, respectively.

Details

This functions creates the model in the JAGS dialect of the BUGS language. The output of this function constitutes the argument model.file of jags (in the R-package R2jags) via the textConnection function.

prepare_nodesplit inherits measure, model, and assumption from the run_model function. For a binary outcome, when measure is "RR" (relative risk) or "RD" (risk difference) in run_model, prepare_nodesplit currently considers the WinBUGS code for the odds ratio.

The split nodes have been automatically selected via the mtc.nodesplit.comparisons function of the R-package gemtc. See 'Details' in run_nodesplit.

Value

An R character vector object to be passed to run_nodesplit through the textConnection function as the argument object.

Author(s)

Loukia M. Spineli

References

Dias S, Welton NJ, Caldwell DM, Ades AE. Checking consistency in mixed treatment comparison meta-analysis. Stat Med 2010;29(7-8):932–44. doi: 10.1002/sim.3767

Spineli LM, Kalyvas C, Papadimitropoulou K. Continuous(ly) missing outcome data in network meta-analysis: a one-stage pattern-mixture model approach. Stat Methods Med Res 2021;30(4):958–75. doi: 10.1177/0962280220983544

Spineli LM. An empirical comparison of Bayesian modelling strategies for missing binary outcome data in network meta-analysis. BMC Med Res Methodol 2019;19(1):86. doi: 10.1186/s12874-019-0731-y

See Also

jags, run_model, mtc.nodesplit.comparisons, run_nodesplit, textConnection