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In broad usage, the "practical clinical significance" answers the question, how effective is the intervention or treatment, or how much change does the treatment cause. In terms of testing clinical treatments, practical significance optimally yields quantified information about the importance of a finding, using metrics such as effect size, number needed to treat (NNT), and preventive fraction ...
Pupillometry, the measurement of pupil size and reactivity, is a key part of the clinical neurological exam for patients with a wide variety of neurological injuries. It is also used in psychology . [ 1 ] [ 2 ]
Psychometrics is a field of study within psychology concerned with the theory and technique of measurement.Psychometrics generally covers specialized fields within psychology and education devoted to testing, measurement, assessment, and related activities. [1]
(This is true of measures of all types—yardsticks might measure houses well yet have poor reliability when used to measure the lengths of insects.) Reliability may be improved by clarity of expression (for written assessments), lengthening the measure, [9] and other informal means. However, formal psychometric analysis, called item analysis ...
[1] A psychological test is often designed to measure unobserved constructs, also known as latent variables. Psychological tests can include a series of tasks, problems to solve, and characteristics (e.g., behaviors, symptoms) the presence of which the respondent affirms/denies to varying degrees.
Some journals encouraged authors to do more detailed analysis than just a statistical significance test. In social psychology, the journal Basic and Applied Social Psychology banned the use of significance testing altogether from papers it published, [53] requiring authors to use other measures to evaluate hypotheses and impact. [54] [55]
Significance testing has been the favored statistical tool in some experimental social sciences (over 90% of articles in the Journal of Applied Psychology during the early 1990s). [38] Other fields have favored the estimation of parameters (e.g. effect size).
Repeated measures analysis of variance (rANOVA) is a commonly used statistical approach to repeated measure designs. [3] With such designs, the repeated-measure factor (the qualitative independent variable) is the within-subjects factor, while the dependent quantitative variable on which each participant is measured is the dependent variable.