Calculate sensitivity index and bias based on signal detection theory. The correction for extreme proportions of zero and one is the "log-linear" rule recommended by Hautus (1995).
Arguments
- data
Raw data of class
data.frame
.- type_signal
The type of signal stimuli. It should be one of the values in the
name_type
column ofdata
.- ...
For future extensions. Should be empty.
- by
The column name(s) in
data
used to be grouped by. If set toNULL
, all data will be treated as from one subject.- name_acc
The column name of the
data
input whose values are user's correctness, in which is anumeric
vector so coded that 1 means scoring correct, 0 means scoring incorrect, and that -1 means no response is made.- name_type
The column name of the
data
input whose values are the stimuli types. Based ontype_signal
, the other types of stimuli will be treated as non-signal stimuli.
Value
A tibble contains sensitivity index and bias (and other temporary measures).