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Sep 3, 2016 · Odds Ratio (OR) is a measure of association between exposure and an outcome. The OR represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure. Important points about Odds ratio: Calculated in case-control studies as the incidence of outcome is not known.
Probability refers to the likelihood of an event occurring. It can be expressed as a number (0.5) or a percentage (50%). Statistical tests allow psychologists to work out the probability that their results could have occurred by chance, and in general psychologists use a probability level of 0.05.
To calculate the probability of an event, which here is defined as rolling a 1 on an unbiased die, we need to know two things: how many outcomes satisfy the criteria of our event (stated different, how many outcomes would count as what we are looking for) and the total number of outcomes possible.
- Introduction
- Continuous Reinforcement
- Partial (intermittent) Reinforcement Schedules
- Fixed Interval Schedule
- Variable Interval Schedule
- Fixed Ratio Schedule
- Response Rates of Different Reinforcement Schedules
- Extinction of Responses Reinforced at Different Schedules
- Implications For Behavioral Psychology
- References
The type of reinforcement schedule used significantly impacts the response rate and resistance to the extinction of the behavior. Research into schedules of reinforcement has yielded important implications for the field of behavioral science, including choice behavior, behavioral pharmacology, and behavioral economics.
Due to the behavior being reinforced every time, the association is easy to make, and learning occurs quickly. However, this also means that extinction occurs quickly after reinforcement is no longer provided.
Unlike continuous schedules, partial schedules only reinforce the desired behavior occasionally rather than all the time. This leads to slower learning since it is initially more difficult to make the association between behavior and reinforcement. However, partial schedules also produce behavior that is more resistant to extinction. Organisms are ...
Such a schedule results in a tendency for organisms to increase the frequency of responses closer to the anticipated time of reinforcement. However, immediately after being reinforced, the frequency of responses decreases. The fluctuation in response rates means that a fixed-interval schedule will produce a scalloped pattern rather than steady rate...
This schedule produces a low, steady response rate since organisms are unaware of the next time they will receive reinforcers.
This kind of schedule results in high, steady rates of response. Organisms are persistent in responding because of the hope that the next response might be one needed to receive reinforcement. This schedule is utilized in lottery games.
Ratio schedules – those linked to a number of responses – produce higher response rates compared to interval schedules. As well, variable schedules produce more consistent behavior than fixed schedules; the unpredictability of reinforcement results in more consistent responses than predictable reinforcement (Myers, 2011).
Resistance to extinction refers to how long a behavior continues to be displayed even after it is no longer being reinforced. A response high in resistance to extinction will take a longer time to become completely extinct. Different schedules of reinforcement produce different levels of resistance to extinction. In general, schedules that reinforc...
Choice Behavior
behaviorists have long been interested in how organisms make choices about behavior – how they choose between alternatives and reinforcers. They have been able to study behavioral choice through the use of concurrent schedules. Through operating two separate schedules of reinforcement (often both variable-interval schedules) simultaneously, researchers are able to study how organisms allocate their behavior to the different options. An important discovery has been the matching law, which stat...
Behavioral Pharmacology
Schedules of reinforcement are used to evaluate preference and abuse potential for drugs. One method used in behavioral pharmacological research to do so is through a progressive ratio schedule. In a progressive ratio schedule, the response requirement is continuously heightened each time after reinforcement is attained. In the case of pharmacology, participants must demonstrate an increasing number of responses in order to attain an injection of a drug (reinforcement). Under a progressive ra...
Behavioral Economics
Operant experiments offer an ideal way to study microeconomic behavior; participants can be viewed as consumers and reinforcers as commodities. Through experimenting with different schedules of reinforcement, researchers can alter the availability or price of a commodity and track how response allocation changes as a result. For example, changing the ratio schedule (increasing or decreasing the number of responses needed to receive the reinforcer) is a way to study elasticity. Another example...
Ferster, C. B., & Skinner, B. F. (1957). Schedules of reinforcement. New York: Appleton-Century-Crofts. Morgan, D. L. (2010). Schedules of Reinforcement at 50: A Retrospective Appreciation. The Psychological Record; Heidelberg, 60(1), 151–172. Myers, David G. (2011). Psychology(10th ed.). Worth Publishers. What Influences My Behavior? The Matching ...
The odds ratio is used when one of two possible events or outcomes are measured, and there is a supposed causative factor. The odds ratio is a versatile and robust statistic. For example, it can calculate the odds of an event happening given a particular treatment intervention (1).
- Mary L. McHugh
- 2009
Oct 27, 2017 · The odds of an event represent the ratio of the (probability that the event will occur) / (probability that the event will not occur). This could be expressed as follows: Odds of event = Y / (1-Y) So, in this example, if the probability of the event occurring = 0.80, then the odds are 0.80 / (1-0.80) = 0.80/0.20 = 4 (i.e., 4 to 1). If a race ...
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Aug 28, 2019 · Example 5.12. The odds in favour of an event are 2:3 find the probability of the occurrence of this event. Solution. Let E be the event then the odds in favour of the event \(E = \frac{n(E)}{{n(E^{c} )}} = \frac{2}{3}\)
