Description Usage Arguments Value Author(s) References See Also Examples
This function selects suitable bits of JAGS code to build the model file encoding the selected distributional assumptions for the cost and effectiveness variables (and for the selection model)
1 | writeModel(dist.c, dist.e, dist.d, model.file)
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dist.c |
A text string defining the selected distribution for the costs. Available options are Gamma ("gamma"), log-Normal ("logn") and Normal ("norm") |
dist.e |
A text string defining the selected distribution for the measure of effectiveness. Available options are Beta ("beta"), Gamma ("gamma"), Bernoulli ("bern") and Normal ("norm") |
dist.d |
A text string defining the selection model. Possible choices are "cov.cauchy" or "cov.norm" (used when individual covariates are available and can be used to estimate the probability of zero costs) and "int" (when no covariate is available and an intercept-only model is fitted). The function writes a text file in the current working directory, including the relevant bits of code, that can be then passed to the call to the function jags to run the MCMC simulations in background |
model.file |
A string with the name of the model file to which the JAGS code is saved |
Writes out the file with the selected distributional assumptions to the file "model.txt" in the current working directory
Gianluca Baio
Baio G. (2013). Bayesian models for cost-effectiveness analysis in the presence of structural zero costs. http://arxiv.org/pdf/1307.5243v1.pdf
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