Summarise Multi-State Occupation Probabilities over time

Usage

summariseMultistateProbabilities(
  cohort,
  trans,
  strata = list(),
  followUpDays = Inf,
  eventDate = "cohort_start_date",
  censorDate = NULL,
  stateHierarchy = character(),
  stateStep = 0.01
)

Arguments

cohort: A cohort_table object containing one cohort for each state in the multi-state model. Cohort names must match the state names in trans.
trans: Transition matrix describing the states and transitions in the multi-state model. If S is the number of states in the multi-state model, trans should be an S x S matrix, with (i,j)-element a positive integer if a transition from i to j is possible in the multi-state model, NA otherwise. In particular, all diagonal elements should be NA. The integers indicating the possible transitions in the multi-state model should be sequentially numbered, 1,...,K, with K the number of transitions.
strata: List of character vectors defining stratifications. Each character vector identifies one or more columns in cohort; a separate model is fitted for each stratification. The value of strata can not change in each individual.
followUpDays: Maximum number of days of follow-up for which to estimate state occupation probabilities. Use Inf to include all available follow-up.
eventDate: Name of the date column in cohort that identifies when an individual enters a state.
censorDate: Name of the date column in cohort that identifies the end of follow-up, inclusive. If NULL, the end of each individual's observation period is used.
stateHierarchy: Character vector of state names in the order used to resolve states that occur on the same date, with earlier entries occurring first. An empty character vector applies no hierarchy.
stateStep: Numeric increment used to separate states that occur on the same date according to stateHierarchy.

Value

A <summarised_result> object with result_type = "summarise_multistate_probabilities" that contains the multistate probabilities.