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Item Analysis
Within psychometrics, Item analysis refers to statistical methods used for selecting 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. In all cases, however, the purpose of item analysis is to produce a relatively short list of items (that is, questions to be included in an interview or questionnaire) that constitute a pure but comprehensive test of one or a few psychological constructs. To carry out the analysis, a large pool of candidate items, all of which show some degree of face validity, are given to a large sample of participants who are representative of the target population. Ideally, there should be at least 10 times as many candidate items as the desired final length of the test, and several times more people in the sample than there are items in the pool. Researchers ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Psychometrics
Psychometrics is a field of study within psychology concerned with the theory and technique of measurement. Psychometrics generally refers to specialized fields within psychology and education devoted to testing, measurement, assessment, and related activities. Psychometrics is concerned with the objective measurement of latent constructs that cannot be directly observed. Examples of latent constructs include intelligence, introversion, mental disorders, and educational achievement. The levels of individuals on nonobservable latent variables are inferred through mathematical modeling based on what is observed from individuals' responses to items on tests and scales. Practitioners are described as psychometricians, although not all who engage in psychometric research go by this title. Psychometricians usually possess specific qualifications such as degrees or certifications, and most are psychologists with advanced graduate training in psychometrics and measurement theory. I ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Classical Test Theory
Classical test theory (CTT) is a body of related psychometric theory that predicts outcomes of psychological testing such as the difficulty of items or the ability of test-takers. It is a theory of testing based on the idea that a person's observed or obtained score on a test is the sum of a true score (error-free score) and an error score. Generally speaking, the aim of classical test theory is to understand and improve the reliability of psychological tests. ''Classical test theory'' may be regarded as roughly synonymous with ''true score theory''. The term "classical" refers not only to the chronology of these models but also contrasts with the more recent psychometric theories, generally referred to collectively as item response theory, which sometimes bear the appellation "modern" as in "modern latent trait theory". Classical test theory as we know it today was codified by Novick (1966) and described in classic texts such as Lord & Novick (1968) and Allen & Yen (1979/2002). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rasch Model
The Rasch model, named after Georg Rasch, is a psychometric model for analyzing categorical data, such as answers to questions on a reading assessment or questionnaire responses, as a function of the trade-off between the respondent's abilities, attitudes, or personality traits, and the item difficulty. For example, they may be used to estimate a student's reading ability or the extremity of a person's attitude to capital punishment from responses on a questionnaire. In addition to psychometrics and educational research, the Rasch model and its extensions are used in other areas, including the health profession, agriculture, and market research The mathematical theory underlying Rasch models is a special case of item response theory. However, there are important differences in the interpretation of the model parameters and its philosophical implications that separate proponents of the Rasch model from the item response modeling tradition. A central aspect of this divide relates to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Face Validity
Face validity is the extent to which a test is subjectively viewed as covering the concept it purports to measure. It refers to the transparency or relevance of a test as it appears to test participants. In other words, a test can be said to have face validity if it "looks like" it is going to measure what it is supposed to measure. For instance, if a test is prepared to measure whether students can perform multiplication, and the people to whom it is shown all agree that it looks like a good test of multiplication ability, this demonstrates face validity of the test. Face validity is often contrasted with content validity and construct validity. Some people use the term face validity to refer only to the validity of a test to observers who are not expert in testing methodologies. For instance, if a test is designed to measure whether children are good spellers, and parents are asked whether the test is a good test, this measures the face validity of the test. If an expert is asked ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cronbach's Alpha
Cronbach's alpha (Cronbach's \alpha), also known as tau-equivalent reliability (\rho_T) or coefficient alpha (coefficient \alpha), is a reliability coefficient that provides a method of measuring internal consistency of tests and measures. Numerous studies warn against using it unconditionally, and note that reliability coefficients based on structural equation modeling (SEM) are in many cases a suitable alternative.Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach's alpha. Psychometrika, 74(1), 107–120. Green, S. B., & Yang, Y. (2009). Commentary on coefficient alpha: A cautionary tale. Psychometrika, 74(1), 121–135. Revelle, W., & Zinbarg, R. E. (2009). Coefficients alpha, beta, omega, and the glb: Comments on Sijtsma. Psychometrika, 74(1), 145–154. Cho, E., & Kim, S. (2015). Cronbach's coefficient alpha: Well known but poorly understood. Organizational Research Methods, 18(2), 207–230. Raykov, T., & Marcoulides, G. A. (2017). Thanks ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |