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A less-than-perfect test–retest reliability causes test–retest variability. Such variability can be caused by, for example, intra-individual variability and inter-observer variability . A measurement may be said to be repeatable when this variation is smaller than a predetermined acceptance criterion.
The correlation between scores on the two alternate forms is used to estimate the reliability of the test. This method provides a partial solution to many of the problems inherent in the test-retest reliability method. For example, since the two forms of the test are different, carryover effect is less of a problem. Reactivity effects are also ...
The name of this formula stems from the fact that is the twentieth formula discussed in Kuder and Richardson's seminal paper on test reliability. [1] It is a special case of Cronbach's α, computed for dichotomous scores. [2] [3] It is often claimed that a high KR-20 coefficient (e.g., > 0.90) indicates a homogeneous test. However, like ...
In statistics, intra-rater reliability is the degree of agreement among repeated administrations of a diagnostic test performed by a single rater. [ 1 ] [ 2 ] Intra-rater reliability and inter-rater reliability are aspects of test validity .
Test–retest or retest or may refer to: Test–retest reliability; Monitoring (medicine) by performing frequent tests; Doping retest, of an old sports doping sample using improved technology, to allow retrospective disqualification
Example of direct replication and conceptual replication There are two main types of replication in statistics. First, there is a type called “exact replication” (also called "direct replication"), which involves repeating the study as closely as possible to the original to see whether the original results can be precisely reproduced. [ 3 ]
In statistics, inter-rater reliability (also called by various similar names, such as inter-rater agreement, inter-rater concordance, inter-observer reliability, inter-coder reliability, and so on) is the degree of agreement among independent observers who rate, code, or assess the same phenomenon.
Cohen's kappa measures the agreement between two raters who each classify N items into C mutually exclusive categories. The definition of is =, where p o is the relative observed agreement among raters, and p e is the hypothetical probability of chance agreement, using the observed data to calculate the probabilities of each observer randomly selecting each category.