Runs one or more strategy. When more than one strategy is provided, all strategies should have the same states and state value names.
Usage
run_model(
...,
parameters = define_parameters(),
init = c(1000L, rep(0L, get_state_number(get_states(list(...)[[1]])) - 1)),
cycles = 1,
method = c("life-table", "beginning", "end"),
cost = NULL,
effect = NULL,
state_time_limit = NULL,
central_strategy = NULL,
inflow = rep(0L, get_state_number(get_states(list(...)[[1]])))
)
run_model_(
uneval_strategy_list,
parameters,
init,
cycles,
method,
cost,
effect,
state_time_limit,
central_strategy,
inflow
)
Arguments
- ...
One or more
uneval_model
object.- parameters
Optional. An object generated by
define_parameters()
.- init
numeric vector or result of
define_init()
, same length as number of states. Number of individuals in each state at the beginning.- cycles
positive integer. Number of Markov Cycles to compute.
- method
Counting method. See details.
- cost
Names or expression to compute cost on the cost-effectiveness plane.
- effect
Names or expression to compute effect on the cost-effectiveness plane.
- state_time_limit
Optional expansion limit for
state_time
, see details.- central_strategy
character. The name of the strategy at the center of the cost-effectiveness plane, for readability.
- inflow
numeric vector or result of
define_inflow()
, similar toinit
. Number of new individuals in each state per cycle.- uneval_strategy_list
List of models, only used by
run_model_()
to avoid using...
.
Details
In order to compute comparisons strategies must be similar (same states and state value names). Thus strategies can only differ through transition matrix cell values and values attached to states (but not state value names).
The initial number of individuals in each state and the number of cycle will be the same for all strategies
state_time_limit
can be specified in 3 different ways:
As a single value: the limit is applied to all states in all strategies. 2. As a named vector (where names are state names): the limits are applied to the given state names, for all strategies. 3. As a named list of named vectors: the limits are applied to the given state names for the given strategies.
Counting method represents where the transition should occur, based on https://journals.sagepub.com/doi/10.1177/0272989X09340585: "beginning" overestimates costs and "end" underestimates costs.
Examples
# running a single model
mod1 <-
define_strategy(
transition = define_transition(
.5, .5,
.1, .9
),
define_state(
cost = 543,
ly = 1
),
define_state(
cost = 432,
ly = 1
)
)
#> No named state -> generating names.
#> No named state -> generating names.
res <- run_model(
mod1,
init = c(100, 0),
cycles = 2,
cost = cost,
effect = ly
)
#> No named model -> generating names.
# running several models
mod2 <-
define_strategy(
transition = define_transition(
.5, .5,
.1, .9
),
define_state(
cost = 789,
ly = 1
),
define_state(
cost = 456,
ly = 1
)
)
#> No named state -> generating names.
#> No named state -> generating names.
res2 <- run_model(
mod1, mod2,
init = c(100, 0),
cycles = 10,
cost = cost,
effect = ly
)
#> No named model -> generating names.