View source: R/run_model_define.R
run_model | R Documentation |
Runs one or more strategy. When more than one strategy is provided, all strategies should have the same states and state value names.
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
)
... |
One or more |
parameters |
Optional. An object generated by
|
init |
numeric vector or result of |
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
|
central_strategy |
character. The name of the strategy at the center of the cost-effectiveness plane, for readability. |
inflow |
numeric vector or result of
|
uneval_strategy_list |
List of models, only used by
|
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.
A list of evaluated models with computed values.
# 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
)
)
res <- run_model(
mod1,
init = c(100, 0),
cycles = 2,
cost = cost,
effect = ly
)
# 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
)
)
res2 <- run_model(
mod1, mod2,
init = c(100, 0),
cycles = 10,
cost = cost,
effect = ly
)
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