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

Description Usage Arguments Examples

View source: R/write_hurdle.R

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

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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

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#Internal function only
#No examples
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Example output



missingHE documentation built on July 1, 2020, 5:50 p.m.