Signal detection theory (SDT) has been applied to analyzing responses to health measures (87–90). For example, detecting pain involves the patient’s ability to perceive the painful stimulus and the tendency to describe the feeling as “painful.” These can both be evaluated experimentally: two types of stimulus are presented in random order—noise alone or noise plus low levels of signal—and the ability of an individual to identify the presence of a signal against the noise is recorded. Applied to pain research, the stimulus is usually an electric shock and the “noise” is a low level of fluctuating current. For each trial, the respondent judges whether the shock was present and from the resulting pattern of true and false-positive responses, two indexes are calculated: discriminal ability and response bias. Using some basic assumptions, it is possible to estimate these two parameters from a person’s rate of hits and false alarms; this is well described by Hertzog (87). In pain research, this analysis has been used to study whether analgesics influence pain by altering discriminability (i.e., by making the stimulus feel less noxious), or by shifting the response bias (i.e., making the respondent less willing to call the feeling “painful”). Studies of this type are further described in Chapter 9. Presented in the form of ROC curves, the results may show the influence of varying rewards or penalties for making correct or incorrect decisions (90–92). SDT analysis has also been applied in studying the effect of age on test scores: may declines in memory scores among old people reflect changes in approach to taking a test (e.g., cautiousness), rather than real reductions in memory (87)?