create_input_mats() is a generic function for creating an object of class
input_mats. Model matrices are constructed based on the
variables specified in the model object and the data specified in input_data.
create_input_mats() is not typically called by users directly, but is
instead used by functions that create model objects (e.g.,
create_IndivCtstmTrans(), create_CohortDtstmTrans(),
create_PsmCurves()).
create_input_mats(object, ...)
# S3 method for class 'lm'
create_input_mats(object, input_data, ...)
# S3 method for class 'flexsurvreg'
create_input_mats(object, input_data, ...)
# S3 method for class 'flexsurvreg_list'
create_input_mats(object, input_data, ...)
# S3 method for class 'partsurvfit'
create_input_mats(object, input_data, ...)
# S3 method for class 'params_lm'
create_input_mats(object, input_data, ...)
# S3 method for class 'params_surv'
create_input_mats(object, input_data, ...)
# S3 method for class 'params_surv_list'
create_input_mats(object, input_data, ...)
# S3 method for class 'multinom'
create_input_mats(object, input_data, ...)
# S3 method for class 'multinom_list'
create_input_mats(object, input_data, ...)
# S3 method for class 'params_mlogit_list'
create_input_mats(object, input_data, ...)An object of the appropriate class.
Further arguments passed to model.matrix().
An object of class expanded_hesim_data returned by
expand.hesim_data(). It is used to look for the variables needed to create
an input matrix for use in a statistical models and the ID variables for
indexing rows in the input matrix.
An object of class input_mats.
library("flexsurv")
strategies <- data.frame(strategy_id = c(1, 2))
patients <- data.frame(patient_id = seq(1, 3),
age = c(45, 47, 60),
female = c(1, 0, 0),
group = factor(c("Good", "Medium", "Poor")))
states <- data.frame(state_id = seq(1, 3),
state_name = factor(paste0("state", seq(1, 3))))
hesim_dat <- hesim_data(strategies = strategies,
patients = patients,
states = states)
# Class "lm"
input_data <- expand(hesim_dat, by = c("strategies", "patients", "states"))
medcost_fit <- lm(costs ~ female + state_name, psm4_exdata$costs$medical)
input_mats <- create_input_mats(medcost_fit, input_data)
input_mats
#> An "input_mats" object
#>
#> Column binding the ID variables with all variables contained in the X matrices:
#> strategy_id patient_id state_id (Intercept) female state_namestate2
#> <num> <int> <int> <num> <num> <num>
#> 1: 1 1 1 1 1 0
#> 2: 1 1 2 1 1 1
#> 3: 1 1 3 1 1 0
#> 4: 1 2 1 1 0 0
#> 5: 1 2 2 1 0 1
#> 6: 1 2 3 1 0 0
#> 7: 1 3 1 1 0 0
#> 8: 1 3 2 1 0 1
#> 9: 1 3 3 1 0 0
#> 10: 2 1 1 1 1 0
#> 11: 2 1 2 1 1 1
#> 12: 2 1 3 1 1 0
#> 13: 2 2 1 1 0 0
#> 14: 2 2 2 1 0 1
#> 15: 2 2 3 1 0 0
#> 16: 2 3 1 1 0 0
#> 17: 2 3 2 1 0 1
#> 18: 2 3 3 1 0 0
#> state_namestate3
#> <num>
#> 1: 0
#> 2: 0
#> 3: 1
#> 4: 0
#> 5: 0
#> 6: 1
#> 7: 0
#> 8: 0
#> 9: 1
#> 10: 0
#> 11: 0
#> 12: 1
#> 13: 0
#> 14: 0
#> 15: 1
#> 16: 0
#> 17: 0
#> 18: 1
#>
#> Number of unique values of ID variables:
#> n_strategies n_patients n_states
#> 2 3 3
#>
# Class "flexsurvreg"
input_data <- expand(hesim_dat, by = c("strategies", "patients"))
fit_wei <- flexsurvreg(formula = Surv(futime, fustat) ~ 1,
data = ovarian, dist = "weibull")
input_mats <- create_input_mats(fit_wei, input_data)
input_mats
#> An "input_mats" object
#>
#> Column binding the ID variables with all variables contained in the X matrices:
#> strategy_id patient_id (Intercept)
#> <num> <int> <num>
#> 1: 1 1 1
#> 2: 1 2 1
#> 3: 1 3 1
#> 4: 2 1 1
#> 5: 2 2 1
#> 6: 2 3 1
#>
#> Number of unique values of ID variables:
#> n_strategies n_patients
#> 2 3
#>