NEWS.md
- sim_ev(), sim_costs(), and sim_qalys() are now exported functions that give users additional flexibility in their modeling pipelines and provide improved documentation for computation of expected values in cohort models. sim_ev() is particularly useful for computing outcomes that depend on time in state other than costs or quality-adjusted life-years (QALYs).
Multiple absorbing states (or none at all) are possible in hesim::CohortDtstm and hesim::IndivCtstm models (previously the final health state was always assumed to be a death state). In cohort models, the absorbing states can be set manually using the absorbing field in the hesim::CohortDtstmTrans class; if not, they are set automatically based on the transition probabilities. The number of health states in state value models (class hesim::StateVals) must equal the number of health states in the transition models less the number of absorbing states.
A new create_CohortDtstmTrans.params_mlogit_list() method allows the transition component of a cohort discrete time state transition model (cDTSTM) to be created directly from multinomial logistic regression parameter objects.
The coefficient elements of parameter objects can be constructed from any object (e.g., data frame) than can be passed to as.matrix() (rather than only from matrices as in previous versions). See, for instance, params_surv().
The coefficient elements of parameter objects can be constructed from any object (e.g., data frame) than can be passed to as.matrix() (rather than only from matrices as in previous versions). See, for instance, params_surv().