select_model_structures: Select model structures
In InnovationValueInitiative/IVI-RA: The IVI-RA model

Select the model structures to use in the IVI-RA individual patient simulation.

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select_model_structures(tx_ihaq = "acr-haq", tx_iswitch = "acr-switch",
  cdmards_haq_model = "lcgm", ttd_cause = "all",
  ttd_dist = "exponential", utility_model = "mixture")

`tx_ihaq`	Model structure relating treatment to HAQ during the first 6 months of treatment. Options, which are equivalent to H1-H3 in the documentation are: `acr-haq` H1: Treatment -> ACR -> HAQ `acr-eular-haq` H2: Treatment -> ACR -> EULAR -> HAQ `haq` H3:Treatment -> HAQ
`tx_iswitch`	Model structure relating treatment to switching during the first 6 months of treatment. Options, which are equivalent to S1-S6 in the documentation are: `acr-switch` S1: Treatment -> ACR -> Switch `acr-das28-switch` S2: Treatment -> ACR -> DAS28 -> Switch `acr-sdai-switch` S3: Treatment -> ACR -> SDAI -> Switch `acr-cdai-switch` S4: Treatment -> ACR -> CDAI -> Switch `das28-switch` S5: Treatment -> DAS28 -> Switch `acr-eular-switch` S6: Treatment -> ACR -> EULAR -> Switch
`cdmards_haq_model`	Model used for long-term HAQ progression. Options are: lcgm Latent class growth model linear Constant linear HAQ progression If `lgcm` is chosen, then a latent class growth model is used for cDMARDs and NBT but a constant annual rate is is assumed for all other therapies; otherwise a constant linear HAQ progression is assumed for all therapies including cDMARDs and NBT.
`ttd_cause`	Cause of treatment discontinuation. Options are: all Treatment discontinuation due to any cause. si Treatment discontinuation due to serious infections
`ttd_dist`	Distribution used to model time to treatment discontinuaton. Options are: exponential Exponential weibull Weibull gompertz Gompertz gamma Gamma llogis Log-logistic lnorm Lognormal gengamma Generalized gamma
`utility_model`	Model used to estimate patient utility as a function of HAQ and patient characteristics. Options are: mixture Hernandez Alava (2013) mixutre model wailoo Wailoo 2006 logistc regression

mod.structs <- select_model_structures(tx_ihaq = c("acr-haq", "acr-eular-haq"),
                                      tx_iswitch = c("acr-switch", "acr-eular-switch"),
                                      cdmards_haq_model = c("lcgm", "linear"),
                                      ttd_cause = c("all", "si"),
                                      ttd_dist = c("gengamma", "exponential"),
                                      utility_model = c("mixture", "wailoo"))
print(mod.structs)