Description
Usage
Arguments
Examples
View source: R/data_read_selection.R
This internal function imports the data and outputs only those variables that are needed to run the model
according to the information provided by the user.
 (
,
model.eff,
model.cost,
model.me,
model.mc,
,
center
)

data 
A data frame in which to find variables supplied in model.eff and model.cost . Among these,
effectiveness, cost and treatment indicator (only two arms) variables must always be provided and named 'e', 'c' and 't' 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 righthand 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.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 righthand 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.me 
A formula expression in conventional R linear modelling syntax. The response must be indicated with the
term 'me'(missing effects) and any covariates used to estimate the probability of missing effects are given on the righthand side.
If there are no covariates, specify 1 on the right hand side. By default, covariates are placed on the "probability" parameter for the missing effects through a logisticlinear model.
Random effects can also be specified for each model parameter.

model.mc 
A formula expression in conventional R linear modelling syntax. The response must be indicated with the
term 'mc'(missing costs) and any covariates used to estimate the probability of missing costs should be given on the righthand side.
If there are no covariates, specify 1 on the right hand side. By default, covariates are placed on the "probability" parameter for the missing costs through a logisticlinear model.
Random effects can also be specified for each model parameter.

type 
Type of missingness mechanism assumed. Choices are Missing At Random (MAR) and Missing Not At Random (MNAR).

center 
Logical. If center is TRUE all the covariates in the model are centered.

 #Internal function only
#no examples
#
#

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