netbenef: Computes net benefit values across a range of...

In agaye/ceeComp: Assessing agreement between cost-effectiveness estimates from differentes sources

Description

The function takes one dataset and a vector of wilingness-to-pay values. The dataset MUST have 4 columns ID, RESPONSE, COST and TREATMENT which hold respectively unique subject identifiers, treatment outcome, treatment cost and 2 treatment arms names. If no values are for wilingness-to-pay 101 default values ranging from 0 to 500,000 are used to compute net befit.

Usage

netbenef(data = NULL, will2pay = NULL, CI = 0.95,
  treatResponse = "beneficial")

Arguments

data	a dataset with 4 columns holding respectively, ID, treatment outcome, treatment cost and treatment arm.
will2pay	a numeric vector of willingness-to-pay thresholds.
CI	confidence interval.
treatResponse	a character, default is beneficial i.e. the treatment resulted in beneficial response; otherwise harmful, the treatement resulted in harmful outcome

Details

to be written

Value

a table with for columns: net benefit, standard error, upper and lower limit

Author(s)

Amadou Gaye & Felix Achana

Examples

{

# load examples datasets
data(dataset1)

# nebefit computation using the default willingness-to-pay thresholds
NB <- netbenef(dataset1)

# display the top 5 records of the output table
NB[1:5,]

}

agaye/ceeComp documentation built on May 10, 2019, 7:32 a.m.