Search results
Results From The WOW.Com Content Network
The term significance does not imply importance here, and the term statistical significance is not the same as research significance, theoretical significance, or practical significance. [ 1 ] [ 2 ] [ 18 ] [ 19 ] For example, the term clinical significance refers to the practical importance of a treatment effect.
Double-loop learning is used when it is necessary to change the mental model on which a decision depends. Unlike single loops, this model includes a shift in understanding, from simple and static to broader and more dynamic, such as taking into account the changes in the surroundings and the need for expression changes in mental models. [3]
This model aims to teach clinical graduate students to adhere to the scientific method when executing their applied practices. The model states that in order to master these techniques, graduate students need to attend seminars and lectures that strengthen their background in psychology, complete monitored field work, and receive research training.
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 ...
Statistical significance measures probability and does not address practical significance. It can be viewed as a criterion for the statistical signal-to-noise ratio . It is important to note that the test cannot prove the hypothesis (of no treatment effect), but it can provide evidence against it.
the first-order and higher-order states are part of the same whole, and the whole complex is what becomes conscious. [1] An example of the second, "part-whole" self-representational theory is Vincent Picciuto's "quotational theory of consciousness" in which consciousness consists of "mentally quoting" a first-order perception. [4]
Statistical thinking is the type of thinking used by statisticians when they encounter a statistical problem. This involves thinking about the nature and quality of the data and, where the data came from, choosing appropriate analyses and models, and interpreting the results in the context of the problem and given the constraints of the data.
In psychology, the I-change model [1] [2] or the integrated model, for explaining motivational and behavioral change, derives from the Attitude – Social Influence – Self-Efficacy Model, integrates ideas of Ajzen's Theory of Planned Behavior, [3] Bandura's Social Cognitive Theory, Prochaska's Transtheoretical Model, [4] the Health Belief Model, [5] and Goal setting [6] theories.