Generate a tidy table of incremental cost-effectiveness ratios (ICERs) given output from
icer() and format for pretty printing with
icer(x, prob = 0.95, k = 50000, labels = NULL, ...) # S3 method for icer format( x, digits_qalys = 2, digits_costs = 0, pivot_from = "strategy", drop_grp = TRUE, pretty_names = TRUE, ... )
An object of class
cea_pw returned by
A numeric scalar in the interval
(0,1) giving the confidence interval.
Default is 0.95 for a 95 percent interval.
Willingness to pay per quality-adjusted life-year.
A list of named vectors containing the values and labels of
variables. The elements of each vector are the values of a variable and the
names are the labels. The names of the list are the names of the variables.
See the output returned by
get_labels() for an example.
Further arguments passed to and from methods. Currently unused.
Number of digits to use to report QALYs.
Number of digits to use to report costs.
Character vector denoting a column or columns used to
"widen" the data. Should either be
or some combination of the three. There will be one column for each value of
the variables in
pivot_from. Default is to widen so there is a column for each treatment
strategy. Set to
NULL if you do not want to widen the table.
TRUE, then the group column will be removed if there is only
one subgroup; other it will be kept. If
FALSE, then the
grp column is never
TRUE, then the columns
value are renamed (if they exist) to
icer() returns an object of class
icer that is a tidy
data.table with the following columns:
The treatment strategy.
The outcome metric.
The point estimate computed as the average across the PSA samples.
The lower limit of the confidence interval.
The upper limit of the confidence interval.
format.icer() formats the table according to the arguments passed.
icer() will report negative ICERs; however,
correctly note whether a treatment strategy is dominated by or dominates the