add_stats assumes the input of essential 2x2 frequency counts
(as a data frame data with variable names "hi", "fa", "mi", and "cr")
and uses them to compute various decision accuracy measures.
add_stats(
data,
sens.w = 0.5,
cost.each = NULL,
cost.outcomes = list(hi = 0, fa = 1, mi = 1, cr = 0)
)A data frame with variables of computed accuracy and cost measures (but dropping inputs).
A data frame with (integer) values named "hi", "fa", "mi", and "cr".
numeric. Sensitivity weight (for computing weighted accuracy, wacc).
numeric. An optional fixed cost added to all outputs (e.g.; the cost of the cue).
list. A list of length 4 named "hi", "fa", "mi", "cr", and
specifying the costs of a hit, false alarm, miss, and correct rejection, respectively.
E.g.; cost.outcomes = listc("hi" = 0, "fa" = 10, "mi" = 20, "cr" = 0) means that a
false alarm and miss cost 10 and 20 units, respectively, while correct decisions incur no costs.
Providing numeric values for cost.each (as a vector) and cost.outcomes (as a named list)
allows computing cost information for the counts of corresponding classification decisions.