Fixed-interval responding under second-order schedules of food presentation or cocaine injection.

Squirrel monkeys operated a key under second-order schedules in which every tenth completion of a 5-minute fixed interval resulted in either presentation of food or intravenous injection of cocaine. When a 2-second light was presented at the completion of the component fixed-interval schedules, positively accelerated responding developed and was maintained in each component. Over a tenfold range of doses of cocaine(30 to 300 microgram/kg/injection) and amounts of food (0.75 to 7.5 g/presentation); the second-order schedule of cocaine injection maintained higher average rates of responding than the second-order schedule of food presentation. Substituting saline for cocaine or eliminating food presentation decreased average rates of responding. When no stimulus change occurred at the completion of the first nine component fixed-interval schedules, but the 2-second light and food presentation or cocaine injection still occurred after the tenth component, only low and relatively constant rates of responding were maintained in each component. Patterns of responding characteristic of 5-minute fixed-interval schedules were maintained by the 2-second light paired with either cocaine injection or food presentation, though the maximum frequency of cocaine injection or food presentation was less than once per 50 minutes.     

On Herrnstein's equation and related forms

In 1970, Herrnstein proposed a simple equation to describe the relation between response and reinforcement rates on interval schedules. Its empirical basis is firm, but its theoretical foundation is still uncertain. Two approaches to the derivation of Herrnstein's equation are discussed. It can be derived as the equilibrium solution to a process model equivalent to familiar linear-operator learning models. Modifications of this approach yield competing power-function formulations. The equation can also be derived from the assumption that response strength is proportional to reinforcement rate, given that there is a ceiling on response rate. The proportional relation can, in turn, be derived from a threshold assumption equivalent to Shimp's “momentary maximizing”. This derivation implies that the two parameters of Herrnstein's equation should be correlated, and may explain its special utility in application to internal schedules.     

A comparison of frequency, interval, and time-sampling methods of data collection

Data representing high, medium, and low response rates in constant and nonconstant patterns were generated by electromechanical equipment to determine whether the same data collected by time-sampling, interval recording, and frequency recording would be represented similarly by each method. Results indicated: (1) that time-sampling provided an extremely inaccurate estimate of responding, and (2) that interval recording accurately represented responding of low and medium rates, but grossly underestimated high-rate responding.     

Force and rate relations in responding during variable-interval reinforcement

Four rats responded on one-minute variable-interval schedules with several variations in peak-force of response required for food reinforcement. Measures of peak force and rate were taken for the responses, which were the downward exertions of force against a static force-transducing operandum. The analysis distinguished responses, a generic class of measured behavior, from criterion responses, an operationally specified subclass required for reinforcement. Absolute rate of response showed no systematic change, but the rate of responses meeting a newly required criterion of peak-force invariably increased through changes in the absolute rate of response, the relative-frequency distributions of peak force, or some combination of both. The relative frequency of responses meeting an elevated force criterion during variable-interval reinforcement exceeded that maintained with the same criterion with continuous reinforcement. The requirement of more effortful responding for reinforcement does not necessarily reduce response rate. Conformity of the behavior to the requirement for reinforcement is the salient effect.     

Choosing what to choose from: Preference for inclusion over exclusion when constructing consideration sets from large choice sets

Decision making is a two‐stage process, consisting of, first, consideration set construction and then final choice. Decision makers can form a consideration set from a choice set using one of two strategies: including the options they wish to further consider or excluding those they do not wish to further consider. The authors propose that decision makers have a relative preference for an inclusion (vs. exclusion) strategy when choosing from large choice sets and that this preference is driven primarily by a lay belief that inclusion requires less effort than exclusion, particularly in large choice sets. Study 1 demonstrates that decision makers prefer using an inclusion (vs. exclusion) strategy when faced with large choice sets. Study 2 replicates the effect of choice set size on preference for consideration set construction strategy and demonstrates that the belief that exclusion is more effortful mediates the relative preference for inclusion in large choice sets. Studies 3 and 4 further support the importance of perceived effort, demonstrating a greater preference for inclusion in large choice sets when decision makers are primed to think about effort (vs. accuracy; Study 3) and when the choice set is perceived as requiring more effort because of more information being presented about each alternative (vs. more alternatives in the choice set; Study 4). Finally, Study 5 manipulates consideration set construction strategy, showing that using inclusion (vs. exclusion) in large choice sets leads to smaller consideration sets, greater confidence in the decision process, and a higher quality consideration set.     

Confidence and Uncertainty in Judgmental Forecasting: Differential Effects of Scenario Presentation

Multiple scenario analysis is used by many organizations for long-term planning, in part because the development of more than one scenario of the future is thought to prevent overconfidence in any one specific forecast. The present study attempts to clarify some of the questions concerning the cognitive effects of scenario presentation by distinguishing between confidence and subjective uncertainty. It examined the impact of different types of scenario information on confidence ratings, credible intervals, and features of forecast series. Subjects (N=186) read either one, two, or no scenario(s) describing potential changes in the level of a stimulus variable, then made forecasts of that variable over the next fifty years. Reading any type of scenario information increased confidence in forecasts; there was no reduction in confidence due to presentation of multiple conflicting scenarios, compared to presentation of only one scenario. Differences in number and in type of scenarios presented did, however, affect subjective uncertainty.     

On the evaluation of one-sided evidence

We examine predictions and judgments of confidence based on one-sided evidence. Some subjects saw arguments for only one side of a legal dispute while other subjects (called ‘jurors’) saw arguments for both sides. Subjects predicted the number of jurors who favored the plaintiff in each case. Subjects who saw only one side made predictions that were biased in favor of that side. Furthermore, they were more confident but generally less accurate than subjects who saw both sides. The results indicate that people do not compensate sufficiently for missing information even when it is painfully obvious that the information available to them is incomplete. A simple manipulation that required subjects to evaluate the relative strength of the opponent's side greatly reduced the tendency to underweigh missing evidence.     

Interval estimation for linear functions of medians in within-subjects and mixed designs

The currently available distribution-free confidence interval for a difference of medians in a within-subjects design requires an unrealistic assumption of identical distribution shapes. A confidence interval for a general linear function of medians is proposed for within-subjects designs that do not assume identical distribution shapes. The proposed method can be combined with a method for linear functions of independent medians to provide a confidence interval for a linear function of medians in mixed designs. Simulation results show that the proposed methods have good small-sample properties under a wide range of conditions. The proposed methods are illustrated with examples, and R functions that implement the new methods are provided.