# Create utility model

Source: `R/utilmod.R`
`create_utilmod.Rd`

Create a model for health state utility given values of utility by health state, treatment, and time sampled from a probability distribution.

    create_utilmod(n = 100, struct, patients, ae_probs,
      params_utility = iviNSCLC::params_utility, ae_duration = c("month",
      "progression"))

## Arguments

n | The number of random observations of the parameters to draw.
struct | A `model_structure` object.
patients | A data table returned from `create_patients`.
ae_probs | An "ae_probs" object as returned by `ae_probs`.
params_utility | Parameter estimates for health state utilities and adverse event disutilities in the same format as `params_utility`.
ae_duration | Duration of time over with disutility from adverse events should accrue. If `"month"`, then disutility accrues over the first month of treatment; if `progression` then disutility accrues until disease progression (i.e., over the entire duration of time spent in stable disease).

## Value

An object of class "StateVals" from the hesim package.

## Examples

    # Treatment sequences
    txseq1 <- txseq(first = "erlotinib",
                    second = c("osimertinib", "PBDC"),
                    second_plus = c("PBDC + bevacizumab", "PBDC + bevacizumab"))
    txseq2 <- txseq(first = "gefitinib",
                    second = c("osimertinib", "PBDC"),
                    second_plus = c("PBDC + bevacizumab", "PBDC + bevacizumab"))
    txseqs <- txseq_list(seq1 = txseq1, seq2 = txseq2)

    # Patient population
    pats <- create_patients(n = 2)

    ## Model structure
    struct <- model_structure(txseqs, dist = "weibull")

    ## Utility model
    n_samples <- 2
    ae_probs <- ae_probs(n = n_samples, struct = struct)
    utilmod <- create_utilmod(n = n_samples, struct = struct, patients = pats,
                              ae_probs = ae_probs)