write_hurdle: An internal function to select which type of hurdle model to...

In missingHE: Missing Outcome Data in Health Economic Evaluation

An internal function to select which type of hurdle model to execute for both effectiveness and costs. Alternatives vary depending on the type of distribution assumed for the effect and cost variables, type of structural value mechanism assumed and independence or joint modelling This function selects which type of model to execute.

Description

An internal function to select which type of hurdle model to execute for both effectiveness and costs. Alternatives vary depending on the type of distribution assumed for the effect and cost variables, type of structural value mechanism assumed and independence or joint modelling This function selects which type of model to execute.

Usage

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

Arguments

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')
type	Type of structural value mechanism assumed. Choices are Structural Completely At Random (SCAR) and Structural At Random (SAR)
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
ind_fixed	Logical; if TRUE independence at the level of the fixed effects between effectiveness and costs is assumed, else correlation is accounted for
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
ind_random	Logical; if TRUE independence at the level of the random effects between effectiveness and costs is assumed, else correlation is accounted for
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
se	Structural value for the effectiveness
sc	Structural value for the costs

Examples

#Internal function only
#No examples
#
#

missingHE documentation built on March 31, 2023, 10:27 p.m.