checks_markov_pick_method: Checks the input to run the Markov cycles and picks correct...

In packDAMipd: Decision Analysis Modelling Package with Parameters Estimation Ability from Individual Patient Level Data

Description

Checks the input to run the Markov cycles and picks correct method

Usage

checks_markov_pick_method(
  current_strategy,
  initial_state,
  discount,
  method,
  half_cycle_correction,
  startup_cost,
  startup_util,
  state_cost_only_prevalent,
  state_util_only_prevalent
)

Arguments

current_strategy	strategy object
initial_state	value of states initially
discount	rate of discount for costs and qalys
method	what type of half cycle correction needed
half_cycle_correction	boolean to indicate half cycle correction
startup_cost	cost of states initially
startup_util	utility of states initially if any
state_cost_only_prevalent	boolean parameter to indicate if the costs for state occupancy is only for those in the state excluding those that transitioned new. This is relevant when the transition cost is provided for eg. in a state with dialysis the cost of previous dialysis is different from the newly dialysis cases.Then the state_cost_only_prevalent should be TRUE
state_util_only_prevalent	boolean parameter to indicate if the utilities for state occupancy is only for those in the state excluding those that transitioned new.

Value

changed method name

Examples

tmat <- rbind(c(1, 2), c(3, 4))
colnames(tmat) <- rownames(tmat) <- c("Healthy", "Dead")
tm <- populate_transition_matrix(2, tmat, c(0.5, 0.5, 0, 1))
a <- health_state("Healthy", 1, 1, 0, FALSE)
b <- health_state("Dead", 1, 0, 0, TRUE)
health_states <- combine_state(a, b)
this.strategy <- strategy(tm, health_states, "intervention")
checks_markov_pick_method(this.strategy, c(1, 0), c(0, 0),
"half cycle correction", TRUE,NULL,NULL)

packDAMipd documentation built on March 3, 2021, 5:07 p.m.