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The Positive and Negative Syndrome Scale (PANSS) is a medical scale used for measuring symptom severity of patients with schizophrenia. It was published in 1987 by Stanley Kay, Lewis Opler, and Abraham Fiszbein. It is widely used in the study of antipsychotic therapy. The scale is the "gold standard" for evaluating the effects of ...
t. e. The Positive and Negative Affect Schedule (PANAS) is a self-report questionnaire that consists of two 10-item scales to measure both positive and negative affect. Each item is rated on a 5-point scale of 1 (not at all) to 5 (very much). The measure has been used mainly as a research tool in group studies, but can be utilized within ...
The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.
Getty. In the 1870s, French actress Sarah Bernhardt caused quite the scandal when she dressed in the style as one of her many ways to "blur gender roles." But the style still didn't pick up until ...
Affect theory is a theory that seeks to organize affects, sometimes used interchangeably with emotions or subjectively experienced feelings, into discrete categories and to typify their physiological, social, interpersonal, and internalized manifestations. The conversation about affect theory has been taken up in psychology, psychoanalysis ...
She wore the oversize outerwear with no pants underneath, simply finishing the laid-back look with red shoes worn with long white socks—a very Hailey Bieber way to usher the no-pants trend into ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. [6] The false positive rate depends on the significance level. The specificity of the test is equal to 1 minus the false positive rate.
Two, if the actual classification is positive and the predicted classification is negative (1,0), this is called a false negative result because the positive sample is incorrectly identified by the classifier as being negative.