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Within psychometrics, Item analysis refers to statistical methods used for selecting test items for inclusion in a psychological test. The concept goes back at least to Guildford (1936). The process of item analysis varies depending on the psychometric model. For example, classical test theory or the Rasch model call for different procedures ...
Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.
[1] [2] [3] Construct validation is the accumulation of evidence to support the interpretation of what a measure reflects. [1] [4] [5] [6] Modern validity theory defines construct validity as the overarching concern of validity research, subsuming all other types of validity evidence [7] [8] such as content validity and criterion validity. [9] [10]
Reliability provides a convenient index of test quality in a single number, reliability. However, it does not provide any information for evaluating single items. Item analysis within the classical approach often relies on two statistics: the P-value (proportion) and the item-total correlation (point-biserial correlation coefficient).
Test validity is the extent to which a test (such as a chemical, physical, or scholastic test) accurately measures what it is supposed to measure.In the fields of psychological testing and educational testing, "validity refers to the degree to which evidence and theory support the interpretations of test scores entailed by proposed uses of tests". [1]
Items are chosen so that they comply with the test specification which is drawn up through a thorough examination of the subject domain. Foxcroft, Paterson, le Roux & Herbst (2004, p. 49) [9] note that by using a panel of experts to review the test specifications and the selection of items the content validity of a test can be improved. The ...
FlexMIRT IRT software is a multilevel, multiple group software package for item analysis, item calibration, and test scoring. The flexMIRT IRT software package fits a variety of unidimensional and multidimensional item response theory models (also known as item factor analysis models) to single-level and multilevel data in any number of groups.
Differential item functioning (DIF) is a statistical property of a test item that indicates how likely it is for individuals from distinct groups, possessing similar abilities, to respond differently to the item. It manifests when individuals from different groups, with comparable skill levels, do not have an equal likelihood of answering a ...