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.
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
)
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')
Distribution assumed for the costs. Current available chocies are: Normal ('norm'), Gamma ('gamma') or LogNormal ('lnorm')
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)
Number of fixed effects for the effectiveness model
Number of fixed effects for the cost model
Number of fixed effects or the missingness indicators model for the effectiveness
Number of fixed effects or the missingness indicators model for the costs
Logical; if TRUE independence between effectiveness and costs is assumed, else correlation is accounted for
Number of random effects for the effectiveness model
Number of random effects for the cost model
Number of random effects or the missingness indicators model for the effectiveness
Number of random effects or the missingness indicators model for the costs
Logical; if TRUE independence at the level of the random effects between effectiveness and costs is assumed, else correlation is accounted for
Random effects formula for the effectiveness model
Random effects formula for the costs model
Random effects formula for the missingness indicators model for the effectiveness
Random effects formula for the missingness indicators model for the costs
#Internal function only
#No examples
#
#
Run the code above in your browser using DataLab