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	Item response theory - Wikipedia, the free encyclopedia
		The term latent is used to emphasise that discrete item responses are taken to be observable manifestations of the trait or attribute, the existence of which is hypothesized and must be inferred from the manifest responses.
		IRT models are used as a basis for statistical estimation of parameters that represent the 'locations' of persons and items on a latent continuum or, more correctly, the magnitude of the latent trait attributable to the persons and items.
		The discrimination parameter of an item is somewhat analogous to a point-biserial correlation.
	en.wikipedia.org /wiki/Item_response_theory (2397 words)

	Item response theory -- Facts, Info, and Encyclopedia article (Site not responding. Last check: 2007-10-22)
		Item response theory designates a body of related (Click link for more info and facts about psychometric) psychometric theory that predict outcomes of psychological (An examination of the characteristics of something) testing such as the difficulty of items or the ability of test-takers.
		Generally speaking, the aim of item response theory is to understand and improve the (The trait of being dependable or reliable) reliability of psychological tests.
		One of the major contributions of item response theory is the extension or the concept of (The trait of being dependable or reliable) reliability.
	www.absoluteastronomy.com /encyclopedia/i/it/item_response_theory.htm (1243 words)

	Item Response Theory
		In IRT, the true score is defined on the latent trait of interest rather than on the test, as is the case in classical test theory.
		The line relating the trait and response is called an item characteristic curve or ICC for short (this is not the same ICC as the intraclass correlation coefficient).
		According to IRT, the parameters of the ICC (that is, a, b, and c) are invariant across populations.
	luna.cas.usf.edu /~mbrannic/files/pmet/irt.htm (3088 words)

	Item Response Theory Method and Application Gaining Support as Assessment Instrument (Site not responding. Last check: 2007-10-22)
		IRT is a model-based version of test theory that uses a mathematical function to describe the relation between a person's standing on a latent trait and his/her item responses.
		Item difficulty refers to the trait level at which an individual has a 50 percent chance of endorsing the item; typically it is the point at which the curve steepens most dramatically.
		Item discriminability refers to how well the item differentiates between individuals of different latent trait levels and is reflected in the slope of the curve at different regions along the horizontal axis.
	www.istss.org /publications/TS/Summer02/Item_Response.htm (879 words)

	Health and Quality of Life Outcomes \| Full text \| Evaluation of the Functional Assessment of Cancer Therapy-General ...
		More recently, item response theory (IRT) measurement models have entered the field and researchers are increasingly enthusiastic for the prospect of deriving better definitions of underlying constructs and the opportunity to turn attention away from static tests and scales to items and the incremental information they provide [7].
		IRT is more useful since it provides more robust item statistics that are independent and invariant over sample populations that vary in the trait measured by the test.
		Potential advantages of using IRT in health outcome assessments are: more comprehensive and accurate evaluation of item characteristics, assessment of group differences in item and scale functioning, evaluation of scales containing items with different response formats, improvement of existing measures, computer adaptive testing (CAT) applications, and evaluation of person fit [29].
	www.hqlo.com /content/1/1/32 (5478 words)

	Latent Trait Analysis and Item Response Theory (IRT) Models
		Their power and flexibility derive from the fact that they are formalized probability models--they include a "theory" that relates the unobserved (latent) construct(s) of interest--educational attainment, disease severity, program effect, etc.--to the observed (manifest) variables that are actually measured.
		Determine which items are biased in the sense of having different meanings or measurement characteristics in different subpopulations.
		Item response theory and the measurement of motor behavior.
	ourworld.compuserve.com /homepages/jsuebersax/lta.htm (1188 words)

	Reliability and Item Analysis
		In this equation, X refers to the respective actual measurement, that is, subject's response to a particular item; tau is commonly used to refer to the true score, and error refers to the random error component in the measurement.
		Technically, the variance of the sum of two items is equal to the sum of the two variances minus (two times) the covariance, that is, the amount of true score variance common to the two items.
		After deleting all items that are not consistent with the scale, we may not be left with enough items to make up an overall reliable scale (remember that, the fewer items, the less reliable the scale).
	www.statsoftinc.com /textbook/streliab.html (2628 words)

	Education Policy Analysis Archives: Vol. 4 No. 17 Taylor & Nolen "Reframing Assessment Concepts"
		By thinking about each item or task and its relationship to the discipline and the unit methods, students went beyond simply practicing item or task writing techniques and had to consider whether the assessment represented the construct (Validity Dimension 1) and whether the assessment was appropriate for the instructional context (Validity Dimension 3).
		Because responses were anonymous, it was not possible to determine the exact number of males and females in the sections nor the number of students who were to be certified in elementary, secondary, or music education.
		Responses to items 4, 6, and 7 (the influence of assessment, validity issues, and reliability issues) were independently coded by three full professors with strong measurement and statistics backgrounds who had previously taught classroom assessment courses.
	olam.ed.asu.edu /epaa/v4n17.html (15708 words)

	University of Melbourne ePrints Repository - The Application of item response theory to measure problem solving ...
		A review of item response theory (IRT) is given to describe the mathematical models, the philosophy and the properties of a number of measurement models.
		Model fit and item fit statistics are also discussed to demonstrate how these can be used as measures of the goodness-of-fit of the data to the model.
		IRT model comparisons are carried out to assess the relative fit of the data to the models.
	eprints.unimelb.edu.au /archive/00000900 (563 words)

	Sunday Seminar 2 Item Response Theory (Site not responding. Last check: 2007-10-22)
		Although classical test theory (CTT) has been the method of choice for constructing achievement, aptitude, and personality tests for decades, CTT has some well-known shortcomings, such as sample-dependent item statistics, item-dependent ability estimates, unconditional standard errors of measurement, and limited utility for computerized adaptive testing.
		Item response theory (IRT) was developed in the 1950s to address some of these shortcomings.
		In the theory part, IRT models for dichotomous and polytomous response data will be introduced, with emphasis on the underlying assumptions and how CTT shortcomings are addressed and resolved.
	www.siop.org /Conferences/05Con/Regbk/sunday_seminar_2.htm (665 words)

	Item Response Theory (Site not responding. Last check: 2007-10-22)
		Item Response Theory (IRT) assumes that there is a correlation between the score gained by a candidate for one item/test (measurable) and their overall ability on the latent trait which underlies test performance (which we want to discover).
		Critically, the 'characteristics' of an item are said to be independent of the ability of the candidates who were sampled.
		Increasing the discrimination of an item causes the gradient of the curve to increase.
	www.jelsim.org /content/applets/item/item.html (362 words)

	Item Response Theory (Site not responding. Last check: 2007-10-22)
		Item Response Theory is the study of test and item scores based on assumptions concerning the mathematical relationship between abilities (or other hypothesized traits) and item responses.
		BILOG Estimates IRT Parameters for the 1-, 2-, or 3-parameter logistic model using marginal maximum-likelihood.
		Fundamentals of Item Response Theory by Ronald Hambleton
	edres.org /irt (417 words)

	Amazon.com: Books: Handbook of Modern Item Response Theory (Site not responding. Last check: 2007-10-22)
		Fundamentals of Item Response Theory (Measurement Methods for the Social Science) by H.
		Item response theory has become an essential component in the toolkit of every researcher in the behavioral sciences.
		As a result, all researchers whose work uses item response theory will find this an indispensable companion to their work and it will be the subject's reference volume for many years to come.
	www.amazon.com /exec/obidos/tg/detail/-/0387946616?v=glance (784 words)

	Item Response Theory Books (Site not responding. Last check: 2007-10-22)
		Item Response Theory for Psychologists Susan E. Embretson and Steven P. Reise.
		Item Response Theory: Parameter Estimation Techniques (Second Edition, Revised and Expanded w/CD) Frank Baker and Seock-Ho Kim.
		Item Response Theory: Principles and Applications Ronald K. Hambleton and Hariharan Swaminathan.
	www.assess.com /Books/b-irt.htm (241 words)

	A Measurement Decision Theory Tutorial
		Classical measurement theory and item response theory are concerned primarily with rank ordering examinees across an ability continuum.
		Key articles in the mastery testing literature of the 1970s employed decision theory (Hambleton and Novick, 1973; Huynh, 1976; van der Linden and Mellenbergh, 1977) and should be re-examined in light of today’s measurement problems.
		Most of the research to date has applied decision theory to testlets or test batteries or as a supplement to item response theory and specific latent class models.
	edres.org /mdt (643 words)

	Outcomes Research - Cancer Health Disparities Collaborative
		Of special interest was an open discussion among representatives of public and private organizations on the utility of developing and supporting public domain item banks and computerized adaptive tests (CATs) for measuring key health domains such as physical functioning, emotional well-being, fatigue, and pain.
		The SPC goals for the conference were to provide an open forum to discuss both the strengths and limitations of IRT methodology and to outline a research agenda for the future of health outcomes measurement.
		Also, an introductory IRT workshop, taught by Dr. Steve Reise, UCLA, was offered the day prior to the start of the conference.
	outcomes.cancer.gov /conference/irt (201 words)

	Item response theory (Site not responding. Last check: 2007-10-22)
		Participants will learn the basic principles of item response theory (IRT).
		The course starts with some theory on IRT, including a comparison with classical test theory.
		The data analyses will be discussed and interpreted on the basis of materials that the trainer will provide.
	www.cito.nl /i_course/itemresp/info.htm (84 words)

	Measurement and Evaluation - Blaine
		Theory of measurement and evaluation; analysis of tests and scales emphasizing statistical and psychological analysis of experimental and standardized tests and scales.
		Norman Campbell's Theory of Fundamental Measurement [as described in Reese, T. The application of the theory of physical measurement to the measurement of psychological magnitudes, with three experimental examples.
		We will emphasize a consideration of the theories and techniques for dimensionalizing the domain but don't want to lose sight of the necessary integration with estimating the parameters of the structural model.
	www2.hawaii.edu /~daniel/616.html (971 words)

	Item Response Theory (Site not responding. Last check: 2007-10-22)
		Estimates IRT Parameters for the 1-, 2-, or 3-parameter logistic model using marginal maximum-likelihood.
		MSP Analyzes dichotomous and polytomous items using nonparametric cumulative item response theory.
		PARELLA Applies parametric IRT theory (i.e., parallelogram analysis) to the measurement of attitudes and preference data.
	www.assess.com /Software/sSumIRT.htm (137 words)

	Book: Item Response Theory for Psychologists (Site not responding. Last check: 2007-10-22)
		Item Response Theory (IRT) is increasingly the psychometric method used for contemporary psychological tests.
		The book is especially useful to psychologists and other social scientists who are familiar with small scale cognitive and personality measures, or to those who want to use IRT to analyze scales used in their own research.
		Polytomous IRT models are given central coverage since many psychological tests use rating scales.
	www.assess.com /Books/b-28192.htm (223 words)

	Item Response Theory (Site not responding. Last check: 2007-10-22)
		This course introduces the fundamental concepts of modern psychometric theory in various application settings, with special emphasis on psychological and educational measurement.
		The dual-objective of this course is to provide a sound theoretical treatment of IRT modeling issues, and to provide hands-on experience with major IRT software packages developed up to date.
		The major topics of this course include: rationale for latent trait theory, taxonomy of item response models, estimation of model parameters, information function and standard error of measurement, model-data fit, Monte Carlo simulation, differential item functioning, test equating, adaptive testing, diagnostic profiling.
	www.gseis.ucla.edu /division/srm/syllabus.irt.html (398 words)

	Publications (Site not responding. Last check: 2007-10-22)
		Beretvas, S.N. and Williams, N.J. The use of hierarchical generalized linear model for item dimensionality assessment.
		Davis, L.L., and Dodd, B.G. Item exposure constraints for testlets in the verbal reasoning section of the MCAT.
		Whittaker, T.A., Fitzpatrick, S.J. Williams, N.J., and Dodd, B.G. IRTGEN: A SAS macro program to generate known trait scores and item responses for commonly used item response theory models.
	www.pearsonedmeasurement.com /research/publications.htm (881 words)

	STAT 778 - Item Response Theory
		Purpose: Upon completion of the course the students will be familiar with the major concepts and theoretical issues in item response theory.
		They will possess the needed technical knowledge to directly consult the more applied research journals in the field at the level expected of a practitioner.
		They will have the background to continue their studies in a reading course preparing them to utilize the more theoretical journals in the field and to conduct research.
	www.stat.sc.edu /curricula/courses/778 (184 words)

	Amazon.ca: Books: Fundamentals of Item Response Theory (Site not responding. Last check: 2007-10-22)
		Using familiar concepts from classical measurement methods and basic statistics, Hambleton and colleagues introduce the basics of item response theory (IRT) and explain the application of IRT methods to problems in test construction, identification of potentially biased test items, test equating, and computerized-adaptive testing.
		The book also includes a thorough discussion of alternative proceduers for estimating IRT parameters, such as maximum likehood estimation, marginal maximum likehood estimation, and Bayesian estimation in such a way that the reader does not need a knowledge of calculus to follow these explanations.
		Including step-by-step numerical examples throughout, the book concludes with an exploration of new directions in IRT research and development.
	www.amazon.ca /exec/obidos/ASIN/0803936478 (208 words)

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