1. Psychometrics
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
An Introduction to Psychometric Theory with Applications in R
What is psychometrics? What is R? Where did it come from, why use it? Basic statistics and graphics TOD An introduction to Psychometric Theory with applications in R William Revelle Department of Psychology Northwestern University Evanston, Illinois USA February, 2013 1 / 71 What is psychometrics? What is R? Where did it come from, why use it? Basic statistics and graphics TOD Overview 1 Overview Psychometrics and R What is Psychometrics What is R 2 Part I: an introduction to R What is R A brief example Basic steps and graphics 3 Day 1: Theory of Data, Issues in Scaling 4 Day 2: More than you ever wanted to know about correlation 5 Day 3: Dimension reduction through factor analysis, principal components analyze and cluster analysis 6 Day 4: Classical Test Theory and Item Response Theory 7 Day 5: Structural Equation Modeling and applied scale construction 2 / 71 What is psychometrics? What is R? Where did it come from, why use it? Basic statistics and graphics TOD Outline of Day 1/part 1 1 What is psychometrics? Conceptual overview Theory: the organization of Observed and Latent variables A latent variable approach to measurement Data and scaling Structural Equation Models 2 What is R? Where did it come from, why use it? Installing R on your computer and adding packages Installing and using packages Implementations of R Basic R capabilities: Calculation, Statistical tables, Graphics Data sets 3 Basic statistics and graphics 4 steps: read, explore, test, graph Basic descriptive and inferential statistics 4 TOD 3 / 71 What is psychometrics? What is R? Where did it come from, why use it? Basic statistics and graphics TOD What is psychometrics? In physical science a first essential step in the direction of learning any subject is to find principles of numerical reckoning and methods for practicably measuring some quality connected with it. -
THE KING JAMES VERSION at 400 Biblical Scholarship in North America
THE KING JAMES VERSION AT 400 Biblical Scholarship in North America Number 26 THE KING JAMES VERSION AT 400 Assessing Its Genius as Bible Translation and Its Literary Influence THE KING JAMES VERSION AT 400 ASSESSING ITS GENIUS AS BIBLE TRANSLATION AND ITS LITERARY INFLUENCE Edited by David G. Burke, John F. Kutsko, and Philip H. Towner Society of Biblical Literature Atlanta THE KING JAMES VERSION AT 400 Assessing Its Genius as Bible Translation and Its Literary Influence Copyright © 2013 by the Society of Biblical Literature All rights reserved. No part of this work may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying and recording, or by means of any information storage or retrieval system, except as may be expressly permit- ted by the 1976 Copyright Act or in writing from the publisher. Requests for permission should be addressed in writing to the Rights and Permissions Offi ce, Society of Biblical Literature, 825 Houston Mill Road, Atlanta, GA 30329 USA. Library of Congress Cataloging-in-Publication Data The King James version at 400 : assessing its genius as Bible translation and its literary influence / edited by David G. Burke, John F. Kutsko, and Philip H. Towner. p. cm. — (Society of Biblical Literature Biblical Scholarship in North America ; number 26) Includes bibliographical references and index. ISBN 978-1-58983-800-0 (hardcover : alk. paper) — ISBN 978-1-58983-798-0 (pbk. : alk. paper) — ISBN 978-1-58983-799-7 (electronic format) 1. Bible. English. Authorized—History—Congresses. 2. Bible. English. Authorized— Influence—Congresses. 3. -
Creative Genius As Inherently Relevant and Beneficial: the View from Mount Olympus
138 Vol. 5, Issue 2, 2018 Theories – Research – Applications Creative Genius as Inherently Relevant and Beneficial: The View from Mount Olympus Dean Keith Simonton University of California, Davis, USA E-mail: [email protected] ARTICLE INFO ABSTRACT Keywords: The author responds to Kaufman’s (2018) target essay from a unique perspective – research on creative genius. Alt- Genius hough the author began studying little-c creativity, he Big-C versus little-c creativity switched to Big-C creativity when he did his doctoral disser- Costs versus benefits tation, and continued that work for the rest of his career. One Creativity training implication of such research is that the relevance of creative Article history: genius cannot be questioned, even if its benefits are some- Received 15 November 2018 times ambiguous (however obviously consequential). Anoth- Received in revised form 20 November 2018 er implication is that creative geniuses do not require training Accepted 20 December 2018 in creativity, whatever usefulness such instruction may pos- sess for everyday creativity. ISSN: 2354-0036 DOI: 10.1515/ctra-2018-0009 James Kaufman (2018) raises some critical issues with which I have some sympathy. Af- ter all, I have made a long-term commitment to creativity research under the assumption that it was and remains a significant topic. Indeed, I started conducting my own original inquiries into creativity in the late 1960s while still an undergraduate (e.g., Simonton, 1980, published a decade later). Thus that initial interest was sparked about a half centu- ry ago! Moreover, I continued that fascination in graduate school despite being warned by various well-intentioned advisors that it was a dead topic that no longer attracted leading- edge research (Simonton, 2002). -
Fatigue and Psychological Distress in the Working Population Psychometrics, Prevalence, and Correlates
Journal of Psychosomatic Research 52 (2002) 445–452 Fatigue and psychological distress in the working population Psychometrics, prevalence, and correlates Ute Bu¨ltmanna,*, Ijmert Kanta, Stanislav V. Kaslb, Anna J.H.M. Beurskensa, Piet A. van den Brandta aDepartment of Epidemiology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands bDepartment of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA Received 11 October 2000 Abstract Objective: The purposes of this study were: (1) to explore the distinct pattern of associations was found for fatigue vs. relationship between fatigue and psychological distress in the psychological distress with respect to demographic factors. The working population; (2) to examine associations with demographic prevalence was 22% for fatigue and 23% for psychological and health factors; and (3) to determine the prevalence of fatigue distress. Of the employees reporting fatigue, 43% had fatigue only, and psychological distress. Methods: Data were taken from whereas 57% had fatigue and psychological distress. Conclusions: 12,095 employees. Fatigue was measured with the Checklist The results indicate that fatigue and psychological distress are Individual Strength, and the General Health Questionnaire (GHQ) common in the working population. Although closely associated, was used to measure psychological distress. Results: Fatigue was there is some evidence suggesting that fatigue and psychological fairly well associated with psychological distress. A separation -
When Psychometrics Meets Epidemiology and the Studies V1.Pdf
When psychometrics meets epidemiology, and the studies which result! Tom Booth [email protected] Lecturer in Quantitative Research Methods, Department of Psychology, University of Edinburgh Who am I? • MSc and PhD in Organisational Psychology – ESRC AQM Scholarship • Manchester Business School, University of Manchester • Topic: Personality psychometrics • Post-doctoral Researcher • Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh. • Primary Research Topic: Cognitive ageing, brain imaging. • Lecturer Quantitative Research Methods • Department of Psychology, University of Edinburgh • Primary Research Topics: Individual differences and health; cognitive ability and brain imaging; Psychometric methods and assessment. Journey of a talk…. • Psychometrics: • Performance of likert-type response scales for personality data. • Murray, Booth & Molenaar (2015) • Epidemiology: • Allostatic load • Measurement: Booth, Starr & Deary (2013); (Unpublished) • Applications: Early life adversity (Unpublished) • Further applications Journey of a talk…. • Methodological interlude: • The issue of optimal time scales. • Individual differences and health: • Personality and Physical Health (review: Murray & Booth, 2015) • Personality, health behaviours and brain integrity (Booth, Mottus et al., 2014) • Looking forward Psychometrics My spiritual home… Middle response options Strongly Agree Agree Neither Agree nor Disagree Strong Disagree Disagree 1 2 3 4 5 Strongly Agree Agree Unsure Disagree Strong Disagree -
Musical Genius--Evolution and Origins of a Concept Author(S): Edward E
Musical Genius--Evolution and Origins of a Concept Author(s): Edward E. Lowinsky Source: The Musical Quarterly, Vol. 50, No. 3 (Jul., 1964), pp. 321-340 Published by: Oxford University Press Stable URL: http://www.jstor.org/stable/741019 . Accessed: 07/04/2013 10:19 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp . JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Oxford University Press is collaborating with JSTOR to digitize, preserve and extend access to The Musical Quarterly. http://www.jstor.org This content downloaded from 143.107.252.222 on Sun, 7 Apr 2013 10:19:11 AM All use subject to JSTOR Terms and Conditions MUSICAL GENIUS - EVOLUTION AND ORIGINS OF A CONCEPT* By EDWARD E. LOWINSKY ARE livingin an age in which musical and technicaldevelop- WE ments suggest the possibilitythat mathematical formulas and computermachines or "chance"I may take over essentialareas of musical creativity."Total organization"or "chance" are two sides of the same process.Both rule out the freeact of creationthat we ordinarilyassociate with the nature of genius. At the same time we observe a deflationof the idea of genius. In a recentbook the Italian architectLeonardo Ricci wrote:"if we say we no longerbelieve in genius,this does not mean only the genius of the past. -
Lexical Creativity and Humor in Translation: on Rabelais’ Linguistic Genius and the Difficulties in Translating His Works
Lexis Journal in English Lexicology 17 | 2021 Humor, creativity and lexical creation Lexical creativity and humor in translation: On Rabelais’ linguistic genius and the difficulties in translating his works Adrienn Gulyás Electronic version URL: https://journals.openedition.org/lexis/5143 DOI: 10.4000/lexis.5143 ISSN: 1951-6215 Publisher Université Jean Moulin - Lyon 3 Electronic reference Adrienn Gulyás, “Lexical creativity and humor in translation: On Rabelais’ linguistic genius and the difficulties in translating his works”, Lexis [Online], 17 | 2021, Online since 15 August 2021, connection on 20 August 2021. URL: http://journals.openedition.org/lexis/5143 ; DOI: https://doi.org/10.4000/ lexis.5143 This text was automatically generated on 20 August 2021. Lexis is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Lexical creativity and humor in translation: On Rabelais’ linguistic genius a... 1 Lexical creativity and humor in translation: On Rabelais’ linguistic genius and the difficulties in translating his works Adrienn Gulyás Introduction 1 Translating humor deriving from lexical creativity, often bound to the form of the source text, is an imposing challenge for literary translators. The main concern of this article is to observe lexical creativity at work in François Rabelais’ Pantagruel and Gargantua and the translators’ solutions to render it in English and Hungarian. First, the theoretical background of the notion of “lexical creativity” will be explored, and a theoretical framework adopted from translation theory for the discussion of examples. In the analysis, a systematic contrastive approach will be applied to compare Screech’s English [2006] and my own Hungarian translations [Pantagruel 2010; Gargantua 2015]. -
Properties and Psychometrics of a Measure of Addiction Recovery Strengths
bs_bs_banner REVIEW Drug and Alcohol Review (March 2013), 32, 187–194 DOI: 10.1111/j.1465-3362.2012.00489.x The Assessment of Recovery Capital: Properties and psychometrics of a measure of addiction recovery strengths TEODORA GROSHKOVA1, DAVID BEST2 & WILLIAM WHITE3 1National Addiction Centre, Institute of Psychiatry, King’s College London, London, UK, 2Turning Point Drug and Alcohol Centre, Monash University, Melbourne, Australia, and 3Chestnut Health Systems, Bloomington, Illinois, USA Abstract Introduction and Aims. Sociological work on social capital and its impact on health behaviours have been translated into the addiction field in the form of ‘recovery capital’ as the construct for assessing individual progress on a recovery journey.Yet there has been little attempt to quantify recovery capital.The aim of the project was to create a scale that assessed addiction recovery capital. Design and Methods. Initial focus group work identified and tested candidate items and domains followed by data collection from multiple sources to enable psychometric assessment of a scale measuring recovery capital. Results. The scale shows moderate test–retest reliability at 1 week and acceptable concurrent validity. Principal component analysis determined single factor structure. Discussion and Conclusions. The Assessment of Recovery Capital (ARC) is a brief and easy to administer measurement of recovery capital that has acceptable psychometric properties and may be a useful complement to deficit-based assessment and outcome monitoring instruments for substance dependent individuals in and out of treatment. [Groshkova T, Best D, White W. The Assessment of Recovery Capital: Properties and psychometrics of a measure of addiction recovery strengths. Drug Alcohol Rev 2013;32:187–194] Key words: addiction, recovery capital measure, assessment, psychometrics. -
PSY610: PSYCHOMETRICS/STATISTICS FALL, 2006 Dr. Gregory T. Smith Teaching Assistant: 105 Kastle Hall Lauren Gudonis 257-6454 L
PSY610: PSYCHOMETRICS/STATISTICS FALL, 2006 Dr. Gregory T. Smith Teaching Assistant: 105 Kastle Hall Lauren Gudonis 257-6454 [email protected] [email protected] office: 111 J Office Hours: Monday and Wednesday 11:00 - 11:45 and by appt. Required Texts: 1. Keppel, G. (2004). Design and Analysis: A Researcher’s Handbook. (4th Edition). Upper Saddle River, N.J.: Pearson/Prentice-Hall, Inc. Course Outline 8/24 1. Introduction. Independent and dependent variables. Correlational and experimental studies. Implications for interpretation of results. Example. Randomization and Random Sampling. 8/29 2. Levels of Measurement. Examples. Relation of levels of measurement to statistical tests. Chart. Three major questions to be answered by statistical analysis: existence, nature, and magnitude of relationships between X and Y (or Y1 and Y2). Introduction to probability. 8/31 3. Probability: an intuitive approach and a formal approach. Independence and conditional probabilities. Introduction to the logic of hypothesis testing. 9/5 4. The logic of hypothesis testing. Introduction to parametric (normal distribution) techniques. One sample goodness of fit test z. Sampling distribution of the mean. Central limit theorem. Standard error of the mean. Lab #1 Introduction to lab. Probability. Definitions, examples, and exercises. Introduction to computer system. Homework #1 assigned. 9/7 5. Logic of hypothesis testing, decision rule, terms, power, Type I and Type II errors. 9/12 6. Student's t test: sampling distribution, procedures, assumptions, degrees of freedom. Unbiased and biased estimates. Directional v. nondirectional tests, confidence intervals, t and z compared. Lab #2 Review material from preceding two lectures; homework; SPSS exercises. 9/14 7. -
Galton, Terman, Cox: the Distinctive Volume II in Genetic Studies Of
GCQXXX10.1177/0016986220921360Gifted Child QuarterlySimonton 921360research-article2020 Article Gifted Child Quarterly 1 –10 Galton, Terman, Cox: © 2020 National Association for Gifted Children Article reuse guidelines: The Distinctive Volume II sagepub.com/journals-permissions DOI:https://doi.org/10.1177/0016986220921360 10.1177/0016986220921360 in Genetic Studies of Genius journals.sagepub.com/home/gcq Dean Keith Simonton1 Abstract With just one exception, all of the volumes in Terman’s Genetic Studies of Genius report the results of a longitudinal study of more than a thousand intellectually gifted children. That single exception is Volume II, Cox’s single-authored The Early Mental Traits of Three Hundred Geniuses, which instead was a retrospective study of 301 eminent creators and leaders, using historiometric methods to estimate their IQs (as well as to assess a subset of 100 on 67 character traits). This article discusses how this volume actually fits with the other four volumes in the set. After giving the historical background, discussion turns to the emergence of Cox’s doctoral dissertation. Then comes a narrative of the aftermath, including subsequent contributions by Cox, Terman, and numerous other researchers extending into the 21st century. The article closes by treating the ways that the intellectually gifted and the historic geniuses are not comparable, thus indicating the need for more recent replications and extensions of her work. Keywords archival, biographical, historical analysis, early childhood, gifted, intelligence Strictly speaking, Lewis M. Terman’s (1925-1959) monu- complete list of impressive big names provided on multiple mental and highly influential Genetic Studies of Genius con- occasions throughout the volume. -
Factor Analysis 1 Factor Analysis
Factor analysis 1 Factor analysis Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. In other words, it is possible, for example, that variations in three or four observed variables mainly reflect the variations in fewer such unobserved variables. Factor analysis searches for such joint variations in response to unobserved latent variables. The observed variables are modeled as linear combinations of the potential factors, plus "error" terms. The information gained about the interdependencies between observed variables can be used later to reduce the set of variables in a dataset. Computationally this technique is equivalent to low rank approximation of the matrix of observed variables. Factor analysis originated in psychometrics, and is used in behavioral sciences, social sciences, marketing, product management, operations research, and other applied sciences that deal with large quantities of data. Factor analysis is related to principal component analysis (PCA), but the two are not identical. Latent variable models, including factor analysis, use regression modelling techniques to test hypotheses producing error terms, while PCA is a descriptive statistical technique[1]. There has been significant controversy in the field over the equivalence or otherwise of the two techniques (see exploratory factor analysis versus principal components analysis). Statistical model Definition Suppose we have a set of observable random variables, with means . Suppose for some unknown constants and unobserved random variables , where and , where , we have Here, the are independently distributed error terms with zero mean and finite variance, which may not be the same for all . -
(ETS) Inductive Reasoning Battery for a High Ability Population
Guide to MITRE/Educational Testing Service (ETS) Inductive Reasoning Battery for a High This publication is based upon work Ability Population supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA) SHARP program, via contract 2015-14120200002-002, and is subject to the Rights in Data – General Clause 52.227-14, Alt. IV (DEC 2007). The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, expressed or implied, of ODNI, IARPA or the U.S. Government or any of the authors’ host affiliations. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright 22 July 2016 annotations therein. ©2016 The MITRE Corporation. All rights reserved. Approved for Public Release; Distribution Unlimited. McLean, VA Case Number 16-2283 2 Table of Contents Disclaimer ....................................................................................................................................... 3 Abstract ........................................................................................................................................... 4 Overview of MITRE/ETS Fluid Reasoning Tests ............................................................................ 5 Test Development Approach ........................................................................................................... 6 Tests ...............................................................................................................................................