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Linear Models For Optimal Test Design


Linear Models For Optimal Test Design
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Linear Models For Optimal Test Design


Linear Models For Optimal Test Design
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Author : W. J. Linden
language : en
Publisher:
Release Date : 2011-03-21

Linear Models For Optimal Test Design written by W. J. Linden and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-21 with categories.




Linear Models For Optimal Test Design


Linear Models For Optimal Test Design
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Author : Wim J. van der Linden
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-01-01

Linear Models For Optimal Test Design written by Wim J. van der Linden and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-01 with Social Science categories.


Over my nearly forty years of teaching and conducting research in the ?eld of psychometric methods, I have seen a number of major technical advances that respond to pressing educational and psychological measu- mentproblems. Thedevelopmentofcriterion-referencedassessmentwasthe ?rst, beginning in the late 1960s with the important work of Robert Glaser and Jim Popham, in response to the need for assessments that considered candidate performance in relation to a well-de?ned body of knowledge and skills rather than in relation to a norm group. The development of criterion-referenced testing methodology with a focus on decision-theoretic concepts and methods, content validity, standard-setting, and the recog- tionofthemeritsofbothcriterion-norm-referencedandcriterion-referenced assessments has tremendously in?uenced current test theory and testing . The second major advance was the introduction of item response-theory (IRT) and associated models and their applications to replace classical test theory (CTT) and related practices. Beginning slowly in the 1940s and 1950s with the pioneering work of Frederic Lord, Allan Birnbaum, and GeorgRasch,bythe1970sthemeasurementjournalswerefullofimportant research studies describing new IRT models, technical advances in model parameter estimation and model ?t, and research on applications of IRT models to equating, test development, the detection of potentially biased test items, and adaptive testing. The overall goal has been to improve and expand measurement practices by overcoming several shortcomings of cl- sicaltesttheory:dependenceoftest-itemstatisticsandreliabilityestimates on examinee samples, dependence of examinee true score estimates on the particular choices of test items, and the limitation in CTT of modeling ex-viii Foreword aminee performance at the test level rather than at the item level.



Linear Models For Optimal Test Design


Linear Models For Optimal Test Design
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Author : Wim J. van der Linden
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-08-09

Linear Models For Optimal Test Design written by Wim J. van der Linden and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-08-09 with Education categories.


Wim van der Linden was just given a lifetime achievement award by the National Council on Measurement in Education. There is no one more prominent in the area of educational testing. There are hundreds of computer-based credentialing exams in areas such as accounting, real estate, nursing, and securities, as well as the well-known admissions exams for college, graduate school, medical school, and law school - there is great need on the theory of testing. This book presents the statistical theory and practice behind constructing good tests e.g., how is the first test item selected, how are the next items selected, and when do you have enough items.



Linear Models In Statistics


Linear Models In Statistics
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Author : Alvin C. Rencher
language : en
Publisher: John Wiley & Sons
Release Date : 2008-01-07

Linear Models In Statistics written by Alvin C. Rencher and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-07 with Mathematics categories.


The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.



Optimization Of Adaptive Test Design Methods For The Determination Of Steady State Data Driven Models In Terms Of Combustion Engine Calibration


Optimization Of Adaptive Test Design Methods For The Determination Of Steady State Data Driven Models In Terms Of Combustion Engine Calibration
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Author : Sandmeier, Nino
language : en
Publisher: Universitätsverlag der TU Berlin
Release Date : 2022-12-01

Optimization Of Adaptive Test Design Methods For The Determination Of Steady State Data Driven Models In Terms Of Combustion Engine Calibration written by Sandmeier, Nino and has been published by Universitätsverlag der TU Berlin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-01 with Technology & Engineering categories.


This thesis deals with the development of a model-based adaptive test design strategy with a focus on steady-state combustion engine calibration. The first research topic investigates the question how to handle limits in the input domain during an adaptive test design procedure. The second area of scope aims at identifying the test design method providing the best model quality improvement in terms of overall model prediction error. To consider restricted areas in the input domain, a convex hull-based solution involving a convex cone algorithm is developed, the outcome of which serves as a boundary model for a test point search. A solution is derived to enable the application of the boundary model to high-dimensional problems without calculating the exact convex hull and cones. Furthermore, different data-driven engine modeling methods are compared, resulting in the Gaussian process model as the most suitable one for a model-based calibration. To determine an appropriate test design method for a Gaussian process model application, two new strategies are developed and compared to state-of-the-art methods. A simulation-based study shows the most benefit applying a modified mutual information test design, followed by a newly developed relevance-based test design with less computational effort. The boundary model and the relevance-based test design are integrated into a multicriterial test design strategy that is tailored to match the requirements of combustion engine test bench measurements. A simulation-based study with seven and nine input parameters and four outputs each offered an average model quality improvement of 36 % and an average measured input area volume increase of 65 % compared to a non-adaptive space-filling test design. The multicriterial test design was applied to a test bench measurement with seven inputs for verification. Compared to a space-filling test design measurement, the improvement could be confirmed with an average model quality increase of 17 % over eight outputs and a 34 % larger measured input area. Diese Arbeit befasst sich mit der Entwicklung einer modellbasierten adaptiven Versuchsplanungsstrategie für die Anwendung in der Applikation des Stationärverhaltens von Verbrennungsmotoren. Der erste Forschungsteil untersucht, wie sich Grenzen im Eingangsraum in die Versuchsplanung eines adaptiven Prozesses einbinden lassen. Ein weiterer Fokus liegt auf der Identifikation einer modellbasierten Versuchsplanung, die eine bestmögliche Verbesserung der globalen Modellqualität hinsichtlich des Prädiktionsfehlers ermöglicht. Es wird ein Grenzraummodell auf Basis der konvexen Hülle unter Zuhilfenahme eines Algorithmus zur Bestimmung eines konvexen Konus entwickelt, das als Grundlage für eine Versuchsplanung in beschränkten Eingangsräumen verwendet wird. Um die Anwendbarkeit bei hochdimensionalen Problemstellungen zu gewährleisten, wird ein Verfahren vorgestellt, das eine Berechnung auch ohne die Bestimmung der exakten konvexen Hülle und konvexen Konen ermöglicht. Des Weiteren werden verschiedene Methoden zur datengetriebenen Modellbildung des Verbrennungsmotors verglichen, wobei das Gauß-Prozess Modell als die geeignetste Modellierungsmethode hervorgeht. Um die bestmögliche Versuchsplanungsmethode bei der Anwendung des Gauß-Prozess Modells zu ermitteln, werden zwei neue Strategien entwickelt und mit verfügbaren Methoden aus der Literatur verglichen. Eine simulationsbasierte Studie zeigt, dass eine angepasste Mutual Information Methode die besten Ergebnisse liefert. Ein neu entwickeltes relevanzbasiertes Verfahren erreicht die zweitbesten Ergebnisse, bietet aber einen geringeren Berechnungsaufwand als das Mutual Information Verfahren. Das Grenzmodell und das relevanzbasierte Verfahren werden in einem multikriteriellen Versuchsplanungsverfahren zusammengeführt, das an die Anforderungen von Messungen an einem Verbrennungsmotorenprüfstand angepasst ist. In einer simulationsbasierten Studie mit sieben bzw. neun Eingangsparametern und jeweils vier Ausgängen konnte eine durchschnittliche Modellqualitätsverbesserung von 36 % und eine mittlere Vergrößerung des vermessenen Eingangsraumvolumens von 65 % im Vergleich zu einer nichtadaptiven raumfüllenden Versuchsplanung gezeigt werden. Das multikriterielle Versuchsplanungsverfahren wurde anhand von Prüfstandsmessungen mit sieben Eingangsparametern verifiziert. Im Vergleich zu einer raumfüllenden Versuchsplanung konnte eine mittlere Modellqualitätsverbesserung über alle acht Ausgänge von 17 % und ein um 34 % vergrößertes vermessenes Eingangsraumvolumen erreicht werden, wodurch die Ergebnisse der Simulationen bestätigt werden konnten.



Optimal Design Of Experiments


Optimal Design Of Experiments
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Author : Friedrich Pukelsheim
language : en
Publisher: SIAM
Release Date : 1993-01-01

Optimal Design Of Experiments written by Friedrich Pukelsheim and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-01-01 with Mathematics categories.


Optimal Design of Experiments offers a rare blend of linear algebra, convex analysis, and statistics. The optimal design for statistical experiments is first formulated as a concave matrix optimization problem. Using tools from convex analysis, the problem is solved generally for a wide class of optimality criteria such as D-, A-, or E-optimality. The book then offers a complementary approach that calls for the study of the symmetry properties of the design problem, exploiting such notions as matrix majorization and the Kiefer information matrix ordering. The results are illustrated with optimal designs for polynomial fit models, Bayes designs, balanced incomplete block designs, exchangeable designs on the cube, rotatable designs on the sphere, and many other examples. Since the book's initial publication in 1993, readers have used its methods to derive optimal designs on the circle, optimal mixture designs, and optimal designs in other statistical models. Using local linearization techniques, the methods described in the book prove useful even for nonlinear cases, in identifying practical designs of experiments. Audience: anyone involved in planning statistical experiments, including mathematical statisticians, applied statisticians, and mathematicians interested in matrix optimization problems.



Statistical Models For Test Equating Scaling And Linking


Statistical Models For Test Equating Scaling And Linking
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Author : Alina von Davier
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-10-19

Statistical Models For Test Equating Scaling And Linking written by Alina von Davier and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-19 with Education categories.


The goal of this book is to emphasize the formal statistical features of the practice of equating, linking, and scaling. The book encourages the view and discusses the quality of the equating results from the statistical perspective (new models, robustness, fit, testing hypotheses, statistical monitoring) as opposed to placing the focus on the policy and the implications, which although very important, represent a different side of the equating practice. The book contributes to establishing “equating” as a theoretical field, a view that has not been offered often before. The tradition in the practice of equating has been to present the knowledge and skills needed as a craft, which implies that only with years of experience under the guidance of a knowledgeable practitioner could one acquire the required skills. This book challenges this view by indicating how a good equating framework, a sound understanding of the assumptions that underlie the psychometric models, and the use of statistical tests and statistical process control tools can help the practitioner navigate the difficult decisions in choosing the final equating function. This book provides a valuable reference for several groups: (a) statisticians and psychometricians interested in the theory behind equating methods, in the use of model-based statistical methods for data smoothing, and in the evaluation of the equating results in applied work; (b) practitioners who need to equate tests, including those with these responsibilities in testing companies, state testing agencies, and school districts; and (c) instructors in psychometric, measurement, and psychology programs.



Handbook Of Test Development


Handbook Of Test Development
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Author : Suzanne Lane
language : en
Publisher: Routledge
Release Date : 2015-10-08

Handbook Of Test Development written by Suzanne Lane and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-08 with Education categories.


The second edition of the Handbook of Test Development provides graduate students and professionals with an up-to-date, research-oriented guide to the latest developments in the field. Including thirty-two chapters by well-known scholars and practitioners, it is divided into five sections, covering the foundations of test development, content definition, item development, test design and form assembly, and the processes of test administration, documentation, and evaluation. Keenly aware of developments in the field since the publication of the first edition, including changes in technology, the evolution of psychometric theory, and the increased demands for effective tests via educational policy, the editors of this edition include new chapters on assessing noncognitive skills, measuring growth and learning progressions, automated item generation and test assembly, and computerized scoring of constructed responses. The volume also includes expanded coverage of performance testing, validity, fairness, and numerous other topics. Edited by Suzanne Lane, Mark R. Raymond, and Thomas M. Haladyna, The Handbook of Test Development, 2nd edition, is based on the revised Standards for Educational and Psychological Testing, and is appropriate for graduate courses and seminars that deal with test development and usage, professional testing services and credentialing agencies, state and local boards of education, and academic libraries serving these groups.



Moda 9 Advances In Model Oriented Design And Analysis


Moda 9 Advances In Model Oriented Design And Analysis
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Author : Alessandra Giovagnoli
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-10

Moda 9 Advances In Model Oriented Design And Analysis written by Alessandra Giovagnoli and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-10 with Mathematics categories.


Statisticians and experimentalists will find the latest trends in optimal experimental design research. Some papers are pioneering contributions, leading to new open research problems. It is a colection of peer reviewed papers.



Handbook Of Item Response Theory


Handbook Of Item Response Theory
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Author : Wim J. van der Linden
language : en
Publisher: CRC Press
Release Date : 2017-03-31

Handbook Of Item Response Theory written by Wim J. van der Linden and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-31 with Mathematics categories.


Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume Two: Statistical Tools presents classical and modern statistical tools used in item response theory (IRT). While IRT heavily depends on the use of statistical tools for handling its models and applications, systematic introductions and reviews that emphasize their relevance to IRT are hardly found in the statistical literature. This second volume in a three-volume set fills this void. Volume Two covers common probability distributions, the issue of models with both intentional and nuisance parameters, the use of information criteria, methods for dealing with missing data, and model identification issues. It also addresses recent developments in parameter estimation and model fit and comparison, such as Bayesian approaches, specifically Markov chain Monte Carlo (MCMC) methods.