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Create an JAGS model for Bayesian sensitivity analysis

Source: R/bayesian_causens.R
create_jags_model.Rd

Creates a JAGS model available as a string, or .txt file, where priors are initialized to be uninformative by default.

Usage

create_jags_model(binary_outcome, beta_uy, alpha_uz)

Arguments

binary_outcome

Boolean indicating whether the outcome is binary.

beta_uy

Prior distribution for the effect of the missing confounder U on the outcome Y.

alpha_uz

Prior distribution for the effect of the missing confounder U on the treatment assignment mechanism Z.

No inputs are given to this function (for now) since data-related information is provided in jags.model() during model initialization.