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

Description Usage Arguments Examples

View source: R/prior_hurdle.R

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

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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

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#Internal function only
#no examples
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missingHE documentation built on July 1, 2020, 5:50 p.m.