prior_hurdle: An internal function to change the hyperprior parameters in...

In missingHE: Missing Outcome Data in Health Economic Evaluation

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

Description

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.

Usage

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
#no examples
#
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missingHE documentation built on March 31, 2023, 10:27 p.m.