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The Impact of Event Scale - Revised (IES-R) is a 22-item self-report questionnaire designed to assess subjective distress caused by traumatic events. It is commonly used in research and clinical settings to measure the severity of symptoms related to post-traumatic stress disorder (PTSD). The IES-R is an updated version of the original Impact ...
Predictive modelling uses statistics to predict outcomes. [1] Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. [2]
Predicted outcome value theory is an alternative to uncertainty reduction theory, which Charles R. Berger and Richard J. Calabrese introduced in 1975. Uncertainty reduction theory states that the driving force in initial interactions is to collect information to predict attitudes and behaviors for future relationship development.
Interfering events are similar to secular trends; in this case it is the short-term events that can produce changes that may introduce bias into estimates of program effect, such as a power outage disrupting communications or hampering the delivery of food supplements may interfere with a nutrition program (Rossi et al., 2004, p273).
In a non-statistical sense, the term "prediction" is often used to refer to an informed guess or opinion.. A prediction of this kind might be informed by a predicting person's abductive reasoning, inductive reasoning, deductive reasoning, and experience; and may be useful—if the predicting person is a knowledgeable person in the field.
Whereas a current forecast reflects expected or predicted utility, the actual outcome of the event reflects experienced utility. Predicted utility is the "weighted average of all possible outcomes under certain circumstances." [57] Experienced utility refers to the perceptions of pleasure and pain associated with an outcome. [5]
This little-known but serious issue can be overcome by using an accuracy measure based on the logarithm of the accuracy ratio (the ratio of the predicted to actual value), given by (). This approach leads to superior statistical properties and also leads to predictions which can be interpreted in terms of the geometric mean.
Even though many studies have established the validity of CGI scales in relation to other commonly used robust rating scales, its efficacy in predicting treatment outcomes is highly debated. Its sensitivity is good enough to differentiate between responders and non-responders in clinical trials of depression, [ 6 ] but its specificity is not ...