A list of tables required for health economic simulation modeling. This object is used to setup models by defining the treatment strategies, target population, and model structure.
hesim_data(strategies, patients, states = NULL, transitions = NULL)
A table of treatment strategies. Must contain the column
strategy_id
denoting a unique strategy. Other columns are variables
describing the characteristics of a treatment strategy.
A table of patients. Must contain the column patient_id
denoting
a unique patient. The number of rows should be equal to the number of patients
in the model. The table may also include columns for grp_id
for subgroups and
patient_wt
specifying the weight to apply to each patient (within a subgroup).
If grp_id
is NULL
, then it is assumed that there is only one subgroup. If
patient_wt
is NULL
. then each patient is given the same weight. Weights
cannot be used in individual-level models because each patient should be
weighted equally; that is, weights can only be specified in cohort models.
Weights within subgroups are normalized to sum to one. Other columns are
variables describing the characteristics of a patient.
A table of health states. Must contain the column
state_id
, which denotes a unique health state. The number of rows should
be equal to the number of health states in the model. Other columns can describe the
characteristics of a health state.
A table of health state transitions. Must contain the column
transition_id
, which denotes a unique transition; from
, which denotes
the starting health state; and to
which denotes the state that will be
transitioned to.
Returns an object of class hesim_data
, which is a list of data tables for
health economic simulation modeling.
Each table must either be a data.frame
or data.table
. All ID variables
within each table must be numeric vectors of integers and should be of the form
1,2,...N where N is the number of unique values of the ID variable.
strategies <- data.frame(strategy_id = c(1, 2))
patients <- data.frame(patient_id = seq(1, 3), age = c(65, 50, 75),
gender = c("Female", "Female", "Male"))
states <- data.frame(state_id = seq(1, 3),
state_var = c(2, 1, 9))
hesim_dat <- hesim_data(strategies = strategies,
patients = patients,
states = states)