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

In missingHE: Missing Outcome Data in Health Economic Evaluation

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.

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

write_selection_long(
  dist_u,
  dist_c,
  type,
  pu_fixed,
  pc_fixed,
  zu_fixed,
  zc_fixed,
  ind_fixed,
  ind_time_fixed,
  pu_random,
  pc_random,
  zu_random,
  zc_random,
  ind_random,
  model_u_random,
  model_c_random,
  model_mu_random,
  model_mc_random
)

Arguments

dist_u	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)
pu_fixed	Number of fixed effects for the effectiveness model
pc_fixed	Number of fixed effects for the cost model
zu_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 at the same time is assumed, else correlation is accounted for
ind_time_fixed	Logical; if TRUE independence between effectiveness and costs over time is assumed, else an AR1 correlation structure is accounted for
pu_random	Number of random effects for the effectiveness model
pc_random	Number of random effects for the cost model
zu_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_u_random	Random effects formula for the effectiveness model
model_c_random	Random effects formula for the costs model
model_mu_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

#Internal function only
#No examples
#
#

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