data_read_hurdle: A function to read and re-arrange the data in different ways...

In missingHE: Missing Outcome Data in Health Economic Evaluation

A function to read and re-arrange the data in different ways for the hurdle model

Description

This internal function imports the data and outputs only those variables that are needed to run the hurdle model according to the information provided by the user.

Usage

data_read_hurdle(
  data,
  model.eff,
  model.cost,
  model.se,
  model.sc,
  se,
  sc,
  cov_matrix,
  type,
  center,
  fixed_e,
  fixed_c,
  random_e,
  random_c,
  trt_lev,
  trt_pos
)

Arguments

data	A data frame in which to find variables supplied in model.eff, model.cost (model formulas for effects and costs) and model.se, model.sc (model formulas for the structural effect and cost models) . Among these, effectiveness, cost and treatment indicator variables must always be provided and named 'e', 'c' and 'trt' respectively.
model.eff	A formula expression in conventional R linear modelling syntax. The response must be a health economics effectiveness outcome ('e') whose name must correspond to that used in data, and any covariates are given on the right-hand side. If there are no covariates, specify 1 on the right hand side. Random effects can also be specified for each model parameter.
model.cost	A formula expression in conventional R linear modelling syntax. The response must be a health economics cost outcome ('c') whose name must correspond to that used in data, and any covariates are given on the right-hand side. If there are no covariates, specify 1 on the right hand side. By default, covariates are placed on the "location" parameter of the distribution through a linear model. Random effects can also be specified for each model parameter.
model.se	A formula expression in conventional R linear modelling syntax. The response must be a health economics effectiveness outcome ('e') whose name must correspond to that used in data, and any covariates used to estimate the probability of structural effects are given on the right-hand side. If there are no covariates, specify 1 on the right hand side. By default, covariates are placed on the "probability" parameter for the structural effects through a logistic-linear model. Random effects can also be specified for each model parameter.
model.sc	A formula expression in conventional R linear modelling syntax. The response must be a health economics cost outcome ('c') whose name must correspond to that used in data, and any covariates used to estimate the probability of structural costs are given on the right-hand side. If there are no covariates, specify 1 on the right hand side. By default, covariates are placed on the "probability" parameter for the structural costs through a logistic-linear model. Random effects can also be specified for each model parameter.
se	Structural value to be found in the effect data defined in data. If set to NULL, no structural value is chosen and a standard model for the effects is run.
sc	Structural value to be found in the cost data defined in data. If set to NULL, no structural value is chosen and a standard model for the costs is run.
cov_matrix	Covariance matrix containing all model covariates.
type	Type of structural value mechanism assumed, either 'SCAR' (Structural Completely At Random) or 'SAR' (Strcutural At Random).
center	Logical. If center is TRUE all the covariates in the model are centered.
fixed_e	Formula of the fixed effects specified in the effectiveness model.
fixed_c	Formula of the fixed effects specified in the cost model.
random_e	Formula of the random effects specified in the effectiveness model.
random_c	Formula of the random effects specified in the cost model.
trt_lev	Levels of the treatment indicator factor.
trt_pos	Numeric position of the treatment indicator within the model formula.

Examples

#Internal function only
#no examples
#
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missingHE documentation built on March 19, 2026, 5:06 p.m.