|
Generalizability Theory
Generalizability theory, or G theory, is a statistical framework for conceptualizing, investigating, and designing reliable observations. It is used to determine the reliability (i.e., reproducibility) of measurements under specific conditions. It is particularly useful for assessing the reliability of performance assessments. It was originally introduced in Cronbach, L.J., Rajaratnam, N., & Gleser, G.C. (1963). Overview In G theory, sources of variation are referred to as ''facets''. Facets are similar to the "factors" used in analysis of variance, and may include persons, raters, items/forms, time, and settings among other possibilities. These facets are potential sources of error and the purpose of generalizability theory is to quantify the amount of error caused by each facet and interaction of facets. The usefulness of data gained from a G study is crucially dependent on the design of the study. Therefore, the researcher must carefully consider the ways in which he/she h ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Observation
Observation is the active acquisition of information from a primary source. In living beings, observation employs the senses. In science, observation can also involve the perception and recording of data via the use of scientific instruments. The term may also refer to any data collected during the scientific activity. Observations can be qualitative, that is, only the absence or presence of a property is noted, or quantitative if a numerical value is attached to the observed phenomenon by counting or measuring. Science The scientific method requires observations of natural phenomena to formulate and test hypotheses. It consists of the following steps: # Ask a question about a natural phenomenon # Make observations of the phenomenon # Formulate a hypothesis that tentatively answers the question # Predict logical, observable consequences of the hypothesis that have not yet been investigated # Test the hypothesis' predictions by an experiment, observational study, field study, or ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reliability (statistics)
In statistics and psychometrics, reliability is the overall consistency of a measure. A measure is said to have a high reliability if it produces similar results under consistent conditions:"It is the characteristic of a set of test scores that relates to the amount of random error from the measurement process that might be embedded in the scores. Scores that are highly reliable are precise, reproducible, and consistent from one testing occasion to another. That is, if the testing process were repeated with a group of test takers, essentially the same results would be obtained. Various kinds of reliability coefficients, with values ranging between 0.00 (much error) and 1.00 (no error), are usually used to indicate the amount of error in the scores." For example, measurements of people's height and weight are often extremely reliable.The Marketing Accountability Standards Board (MASB) endorses this definition as part of its ongoinCommon Language: Marketing Activities and Metrics Pr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lee Cronbach
Lee Joseph Cronbach (April 22, 1916 – October 1, 2001) was an American educational psychologist who made contributions to psychological testing and measurement. At the University of Illinois, Urbana, Cronbach produced many of his works: the "Alpha" paper (Cronbach, 1951), as well as an essay titled The Two Disciplines of Scientific Psychology, in the ''American Psychologist'' magazine in 1957, where he discussed his thoughts on the increasing divergence between the fields of experimental psychology and correlational psychology (to which he himself belonged). Cronbach was the president of the American Psychological Association, president of the American Educational Research Association, Vida Jacks Professor of Education at Stanford University and a member of the United States National Academy of Sciences, the American Academy of Arts and Sciences, and the American Philosophical Society. Cronbach is considered to be "one of the most prominent and influential educational psycholo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Analysis Of Variance
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the ''t''-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means. History While the analysis of variance reached fruition in the 20th century, antecedents extend centuries into the past according to Stigler. These include hypothesis testing, the partitioning of sums of squares, experimental techniques and the additive model. Laplace was performing hypothesis testing ... [...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] |
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] |
