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In biostatistics, strength of evidence is the strength of a conducted study that can be assessed in health care interventions, e.g. to identify effective health care programs and evaluate the quality of the research in health care.
Such evidence is expected to be empirical evidence and interpretable in accordance with the scientific method. Standards for scientific evidence vary according to the field of inquiry, but the strength of scientific evidence is generally based on the results of statistical analysis and the strength of scientific controls. [citation needed]
However, scientific laws are descriptive accounts of how nature will behave under certain conditions. Scientific theories are broader in scope, and give overarching explanations of how nature works and why it exhibits certain characteristics. Theories are supported by evidence from many different sources, and may contain one or several laws. [34]
Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below. In psychometrics , validity has a particular application known as test validity : "the degree to which evidence and theory support the interpretations of test scores" ("as entailed by ...
A large number of hierarchies of evidence have been proposed. Similar protocols for evaluation of research quality are still in development. So far, the available protocols pay relatively little attention to whether outcome research is relevant to efficacy (the outcome of a treatment performed under ideal conditions) or to effectiveness (the outcome of the treatment performed under ordinary ...
There are various standards of evidence, standards showing how strong the evidence must be to meet the legal burden of proof in a given situation, ranging from reasonable suspicion to preponderance of the evidence, clear and convincing evidence, or beyond a reasonable doubt. There are several types of evidence, depending on the form or source.
In science and history, consilience (also convergence of evidence or concordance of evidence) is the principle that evidence from independent, unrelated sources can "converge" on strong conclusions. That is, when multiple sources of evidence are in agreement, the conclusion can be very strong even when none of the individual sources of evidence ...
The original test is analogous to a true/false question; the Neyman–Pearson test is more like multiple choice. In the view of Tukey [60] the former produces a conclusion on the basis of only strong evidence while the latter produces a decision on the basis of available evidence. While the two tests seem quite different both mathematically and ...