Add decision statistics to data (based on frequency counts of a 2x2 matrix of classification outcomes)
Source:R/util_stats.R
add_stats.Rdadd_stats assumes the input of the 4 essential classification outcomes
(as frequency counts in a data frame "data"
with variable names "hi", "fa", "mi", and "cr")
and uses them to compute various decision accuracy measures.
Usage
add_stats(
data,
correction = 0.25,
sens.w = NULL,
my.goal = NULL,
my.goal.fun = NULL,
cost.outcomes = NULL,
cost.each = NULL
)Arguments
- data
A data frame with 4 frequency counts (as integer values, named
"hi","fa","mi", and"cr").- correction
numeric. Correction added to all counts for calculating
dprime. Default:correction = .25.- sens.w
numeric. Sensitivity weight (for computing weighted accuracy,
wacc). Default:sens.w = NULL(to ensure that values are passed by calling function).- my.goal
Name of an optional, user-defined goal (as character string). Default:
my.goal = NULL.- my.goal.fun
User-defined goal function (with 4 arguments
hi fa mi cr). Default:my.goal.fun = NULL.- cost.outcomes
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. Default:cost.outcomes = NULL(to ensure that values are passed by calling function).- cost.each
numeric. An optional fixed cost added to all outputs (e.g., the cost of using the cue). Default:
cost.each = NULL(to ensure that values are passed by calling function).