Signal detection and matching: analyzing choice on concurrent variable-interval schedules.
Pick signal-detection math to measure how well clients discriminate choices, and matching-law math to track payoff changes.
01Research in Context
What this study did
Pigeons pecked two keys that paid off on variable-interval schedules. The team changed how easy it was to tell the schedules apart. They recorded every peck and payoff. Then they scored the data twice: once with signal-detection math and once with matching-law math. The goal was to see which math set told the clearer story.
What they found
Signal-detection indices caught changes in discrimination difficulty. Matching-law indices caught changes in payoff ratios. Each tool worked best for the job it was built for. Neither tool gave the full picture alone.
How this fits with other research
Jones et al. (1998) later showed that discrimination fades the longer a bird stays on one key. Their finding extends Logue (1983) by adding a time clock to the framework. Marcucella et al. (1978) found that signalling a payoff can wreck matching. Logue (1983) builds on that warning by giving you two math kits to spot the wreck. McLean et al. (2018) flipped ratios daily and saw within-session matching fade across days. That update supersedes the static-schedule view in Logue (1983) and tells you to check day-to-day history, not just one session.
Why it matters
When you run concurrent programs in clinic or classroom, pick your metric on purpose. Use signal-detection math when you think the client can't tell the choices apart. Use matching-law math when you change payoff rates. Track time since last switch to catch fading discrimination. These three moves give you faster, cleaner data.
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02At a glance
03Original abstract
Pigeons' pecks on a red key and a green key were followed by access to grain according to pairs of concurrent independent variable-interval schedules in a combined signal detection/matching law paradigm. Pecks on the red key were reinforced by the richer variable-interval schedule if a short-duration tone had been presented; pecks on the green key were reinforced by the richer variable-interval schedule if a long-duration tone had been presented. Pecks on the green key given a short-duration tone, or on the red key given a long-duration tone, were reinforced by the leaner variable-interval schedule. The data were analyzed according to both signal detection's and the matching law's separate measures of, first, the discrimination of the choices and, second, the bias to make one response or another. Increasing the difficulty of the tone-duration discrimination decreased both methods' measures of the discrimination of the choices and did not change both methods' measures of the bias to make one response or another. Changing the leaner variable-interval schedule so that it approached the richer variable-interval schedule decreased signal detection's measure of discrimination but left its measure of response bias and the matching law measures unchanged. Data collected only until a subject's first changeover response following presentation of a long or a short tone showed higher values for both methods' measures of discrimination, no change in signal detection's measure of response bias, and lower values for the matching law's measure of response bias. Relationships between the matching law's and signal detection's methods of analyzing choice are discussed. It is concluded that a signal detection analysis is more efficient for examining changes in the difficulty of a discrimination, whereas a matching law analysis is more effective for examining the effects of changes in relative reinforcer frequency.
Journal of the experimental analysis of behavior, 1983 · doi:10.1901/jeab.1983.39-107