sim_table {BCEA} | R Documentation |

Using the input in the form of MCMC simulations and after having run the health economic model, produces a summary table of the simulations from the cost-effectiveness analysis.

```
sim_table(he, ...)
## S3 method for class 'bcea'
sim_table(he, wtp = 25000, ...)
```

`he` |
A |

`...` |
Additional arguments |

`wtp` |
The value of the willingness to pay threshold to be used in the summary table. |

Produces the following elements:

`table` |
A table with simulation statistics from the economic model |

`names.cols` |
A vector of labels to be associated with each column of the table |

`wtp` |
The selected value of the willingness to pay |

`idx_wtp` |
The index associated with the selected value of the willingness to pay threshold in the grid used to run the analysis |

Gianluca Baio

Baio G, Dawid aP (2011).
“Probabilistic sensitivity analysis in health economics.”
*Stat. Methods Med. Res.*, 1–20.
ISSN 1477-0334, doi:10.1177/0962280211419832, https://pubmed.ncbi.nlm.nih.gov/21930515/.

Baio G (2013).
*Bayesian Methods in Health Economics*.
CRC.

```
# See Baio G., Dawid A.P. (2011) for a detailed description of the
# Bayesian model and economic problem
# Load the processed results of the MCMC simulation model
data(Vaccine)
# Runs the health economic evaluation using BCEA
m <- bcea(e=eff, # defines the variables of
c=cost, # effectiveness and cost
ref=2, # selects the 2nd row of (e, c)
# as containing the reference intervention
interventions=treats, # defines the labels to be associated
# with each intervention
Kmax=50000) # maximum value possible for the willingness
# to pay threshold; implies that k is chosen
# in a grid from the interval (0, Kmax)
# Now can save the simulation exercise in an object using sim_table()
sim_table(m, # uses the results of the economic evaluation
wtp=25000) # selects the particular value for k
```

[Package *BCEA* version 2.4.4 Index]