write_selection: An internal function to select which type of selection model...

Description Usage Arguments Examples

View source: R/write_selection.R

Description

An internal function to select which type of selection model to execute. Alternatives vary depending on the type of distribution assumed for the effect and cost variables, type of missingness mechanism assumed and independence or joint modelling This function selects which type of model to execute.

Usage

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write_selection(
  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_me_random,
  model_mc_random
)

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 missingness mechanism assumed. Choices are Missing At Random (MAR), Missing Not At Random for the effects (MNAR_eff), Missing Not At Random for the costs (MNAR_cost), and Missing Not At Random for both (MNAR)

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 missingness indicators model for the effectiveness

zc_fixed

Number of fixed effects or the missingness indicators model for the costs

ind_fixed

Logical; if TRUE independence 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 missingness indicators model for the effectiveness

zc_random

Number of random effects or the missingness 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_me_random

Random effects formula for the missingness indicators model for the effectiveness

model_mc_random

Random effects formula for the missingness indicators model 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.