prior_hurdle function

An internal function to change the hyperprior parameters in the hurdle model provided by the user depending on the type of structural value mechanism and outcome distributions assumed

This function modifies default hyper prior parameter values in the type of hurdle model selected according to the type of structural value mechanism and distributions for the outcomes assumed.

prior_hurdle(
  type,
  dist_e,
  dist_c,
  pe_fixed,
  pc_fixed,
  ze_fixed,
  zc_fixed,
  model_e_random,
  model_c_random,
  model_se_random,
  model_sc_random,
  pe_random,
  pc_random,
  ze_random,
  zc_random,
  se,
  sc
)

Arguments

• type: Type of structural value mechanism assumed. Choices are Structural Completely At Random (SCAR), and Structural At Random (SAR). For a complete list of all available hyper parameters and types of models see the manual.
• dist_e: distribution assumed for the effects. Current available chocies are: Normal ('norm'), Beta ('beta'), Gamma ('gamma'), Exponential ('exp'), Weibull ('weibull'), Logistic ('logis'), Poisson ('pois'), Negative Binomial ('nbinom') or Bernoulli ('bern')
• dist_c: distribution assumed for the costs. Current available chocies are: Normal ('norm'), Gamma ('gamma') or LogNormal ('lnorm')
• pe_fixed: Number of fixed effects for the effectiveness model
• pc_fixed: Number of fixed effects for the cost model
• ze_fixed: Number of fixed effects or the structural indicators model for the effectiveness
• zc_fixed: Number of fixed effects or the structural indicators model for the costs
• model_e_random: Random effects formula for the effectiveness model
• model_c_random: Random effects formula for the costs model
• model_se_random: Random effects formula for the structural indicators model for the effectiveness
• model_sc_random: Random effects formula for the structural indicators model for the costs
• pe_random: Number of random effects for the effectiveness model
• pc_random: Number of random effects for the cost model
• ze_random: Number of random effects or the structural indicators model for the effectiveness
• zc_random: Number of random effects or the structural indicators model for the costs
• se: Structural value for the effectiveness
• sc: Structural value for the costs

Examples

#Internal function only
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