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The Statistical Approach To Social Measurement
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Book Synopsis The Statistical Approach to Social Measurement by : David J. Bartholomew
Download or read book The Statistical Approach to Social Measurement written by David J. Bartholomew and published by . This book was released on 1996 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on the assumption that the quantities social scientists want to measure, such as attitudes, abilities, price levels, and mobility, can best be represented as unknowns in a statistical model. This method includes both theoretical and practical problems. On the theoretical side, one examines the formulation and testing of an appropriate model and then employs the standard methods of estimation and prediction. On the practical side, one explores the difficulties of implementation deriving from various fields of application. This distinctly statistical approach to social measurement recognizes that in any measuring situation there are two sorts of variables: (1) manifest or indicator variables that one can directly observe, and (2) the latent variables that one cannot observe but wishes to measure. By regarding these all as random variables on common ground, Bartholomew reduces measurement problems to the familiar calculus of probability. Key Features * Argues that social measures should be derived by reference to a statistical (stochastic) model of the process being studied * By analyzing a variety of models, Bartholomew finds the common cords that bind them together in a single whole * Distinctive in its steady attention to the statistical aspects of social measurement and focus
Book Synopsis Making Sense of Statistical Methods in Social Research by : Keming Yang
Download or read book Making Sense of Statistical Methods in Social Research written by Keming Yang and published by SAGE. This book was released on 2010-03-25 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making Sense of Statistical Methods in Social Research is a critical introduction to the use of statistical methods in social research. It provides a unique approach to statistics that concentrates on helping social researchers think about the conceptual basis for the statistical methods they′re using. Whereas other statistical methods books instruct students in how to get through the statistics-based elements of their chosen course with as little mathematical knowledge as possible, this book aims to improve students′ statistical literacy, with the ultimate goal of turning them into competent researchers. Making Sense of Statistical Methods in Social Research contains careful discussion of the conceptual foundation of statistical methods, specifying what questions they can, or cannot, answer. The logic of each statistical method or procedure is explained, drawing on the historical development of the method, existing publications that apply the method, and methodological discussions. Statistical techniques and procedures are presented not for the purpose of showing how to produce statistics with certain software packages, but as a way of illuminating the underlying logic behind the symbols. The limited statistical knowledge that students gain from straight forward ′how-to′ books makes it very hard for students to move beyond introductory statistics courses to postgraduate study and research. This book should help to bridge this gap.
Book Synopsis Statistical Methods in Social Science Research by : S P Mukherjee
Download or read book Statistical Methods in Social Science Research written by S P Mukherjee and published by Springer. This book was released on 2018-10-05 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents various recently developed and traditional statistical techniques, which are increasingly being applied in social science research. The social sciences cover diverse phenomena arising in society, the economy and the environment, some of which are too complex to allow concrete statements; some cannot be defined by direct observations or measurements; some are culture- (or region-) specific, while others are generic and common. Statistics, being a scientific method – as distinct from a ‘science’ related to any one type of phenomena – is used to make inductive inferences regarding various phenomena. The book addresses both qualitative and quantitative research (a combination of which is essential in social science research) and offers valuable supplementary reading at an advanced level for researchers.
Book Synopsis Handbook of Research Design and Social Measurement by : Delbert Charles Miller
Download or read book Handbook of Research Design and Social Measurement written by Delbert Charles Miller and published by David McKay Company. This book was released on 1977 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: " "If a student researcher had only one handbook on their bookshelf, Miller and Salkind's Handbook would certainly have to be it. With the updated material, the addition of the section on ethical issues (which is so well done that I'm recommending it to the departmental representative to the university IRB), and a new Part 4 on "Qualitative Methods," the new Handbook is an indispensable resource for researchers." "Dan Cover, Department of Sociology, Furman University The book considered a "necessity" by many social science researchers and their students has been revised and updated while retaining the features that made it so useful. The emphasis in this new edition is on the tools with which graduate students and more advanced researchers need to become familiar as well as be able to use in order to conduct high quality research.
Book Synopsis Statistical Approaches to Measurement Invariance by : Roger E. Millsap
Download or read book Statistical Approaches to Measurement Invariance written by Roger E. Millsap and published by Routledge. This book was released on 2012-03-29 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the statistical procedures used to detect measurement bias. Measurement bias is examined from a general latent variable perspective so as to accommodate different forms of testing in a variety of contexts including cognitive or clinical variables, attitudes, personality dimensions, or emotional states. Measurement models that underlie psychometric practice are described, including their strengths and limitations. Practical strategies and examples for dealing with bias detection are provided throughout. The book begins with an introduction to the general topic, followed by a review of the measurement models used in psychometric theory. Emphasis is placed on latent variable models, with introductions to classical test theory, factor analysis, and item response theory, and the controversies associated with each, being provided. Measurement invariance and bias in the context of multiple populations is defined in chapter 3 followed by chapter 4 that describes the common factor model for continuous measures in multiple populations and its use in the investigation of factorial invariance. Identification problems in confirmatory factor analysis are examined along with estimation and fit evaluation and an example using WAIS-R data. The factor analysis model for discrete measures in multiple populations with an emphasis on the specification, identification, estimation, and fit evaluation issues is addressed in the next chapter. An MMPI item data example is provided. Chapter 6 reviews both dichotomous and polytomous item response scales emphasizing estimation methods and model fit evaluation. The use of models in item response theory in evaluating invariance across multiple populations is then described, including an example that uses data from a large-scale achievement test. Chapter 8 examines item bias evaluation methods that use observed scores to match individuals and provides an example that applies item response theory to data introduced earlier in the book. The book concludes with the implications of measurement bias for the use of tests in prediction in educational or employment settings. A valuable supplement for advanced courses on psychometrics, testing, measurement, assessment, latent variable modeling, and/or quantitative methods taught in departments of psychology and education, researchers faced with considering bias in measurement will also value this book.
Book Synopsis The Measurement of Association by : Kenneth J. Berry
Download or read book The Measurement of Association written by Kenneth J. Berry and published by Springer. This book was released on 2018-11-02 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research monograph utilizes exact and Monte Carlo permutation statistical methods to generate probability values and measures of effect size for a variety of measures of association. Association is broadly defined to include measures of correlation for two interval-level variables, measures of association for two nominal-level variables or two ordinal-level variables, and measures of agreement for two nominal-level or two ordinal-level variables. Additionally, measures of association for mixtures of the three levels of measurement are considered: nominal-ordinal, nominal-interval, and ordinal-interval measures. Numerous comparisons of permutation and classical statistical methods are presented. Unlike classical statistical methods, permutation statistical methods do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This book takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field. This topic is relatively new in that it took modern computing power to make permutation methods available to those working in mainstream research. Written for a statistically informed audience, it is particularly useful for teachers of statistics, practicing statisticians, applied statisticians, and quantitative graduate students in fields such as psychology, medical research, epidemiology, public health, and biology. It can also serve as a textbook in graduate courses in subjects like statistics, psychology, and biology.
Book Synopsis Statistical Methods for Meta-Analysis by : Larry V. Hedges
Download or read book Statistical Methods for Meta-Analysis written by Larry V. Hedges and published by Academic Press. This book was released on 2014-06-28 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader.Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.
Book Synopsis Statistical Methods for the Analysis of Repeated Measurements by : Charles S. Davis
Download or read book Statistical Methods for the Analysis of Repeated Measurements written by Charles S. Davis and published by Springer Science & Business Media. This book was released on 2008-01-10 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to a wide variety of statistical methods for the analysis of repeated measurements. It is designed to be both a useful reference for practitioners and a textbook for a graduate-level course focused on methods for the analysis of repeated measurements. The important features of this book include a comprehensive coverage of classical and recent methods for continuous and categorical outcome variables; numerous homework problems at the end of each chapter; and the extensive use of real data sets in examples and homework problems.
Book Synopsis Measurement Theory and Applications for the Social Sciences by : Deborah L. Bandalos
Download or read book Measurement Theory and Applications for the Social Sciences written by Deborah L. Bandalos and published by Guilford Publications. This book was released on 2018-01-31 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: Which types of validity evidence should be considered when determining whether a scale is appropriate for a given measurement situation? What about reliability evidence? Using clear explanations illustrated by examples from across the social and behavioral sciences, this engaging text prepares students to make effective decisions about the selection, administration, scoring, interpretation, and development of measurement instruments. Coverage includes the essential measurement topics of scale development, item writing and analysis, and reliability and validity, as well as more advanced topics such as exploratory and confirmatory factor analysis, item response theory, diagnostic classification models, test bias and fairness, standard setting, and equating. End-of-chapter exercises (with answers) emphasize both computations and conceptual understanding to encourage readers to think critically about the material. ÿ
Book Synopsis Using Statistical Methods in Social Science Research by : Soleman H. Abu-Bader
Download or read book Using Statistical Methods in Social Science Research written by Soleman H. Abu-Bader and published by Oxford University Press. This book was released on 2011-07-01 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Using Statistical Methods, Soleman Abu-Bader detects and addresses the gaps between the research and data analysis of the classroom environment and the practitioner's office. This book not only guides social scientists through different tests, but also provides students and researchers alike with information that will help them in their own practice. With focus on the purpose, rationale, and assumptions made by each statistical test, and a plethora of research examples that clearly display their applicability and function in real-world practice, Professor Abu-Bader creates a step-by-step description of the process needed to clearly organize, choose a test or statistical technique, analyze, interpret, and report research findings.
Book Synopsis Statistical Modeling for Management by : Graeme D Hutcheson
Download or read book Statistical Modeling for Management written by Graeme D Hutcheson and published by SAGE. This book was released on 2008-02-12 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing to life the most widely used quantitative measurements and statistical techniques in marketing, this book is packed with user-friendly descriptions, examples and study applications. The process of making marketing decisions is frequently dependent on quantitative analysis and the use of specific statistical tools and techniques which can be tailored and adapted to solve particular marketing problems. Any student hoping to enter the world of marketing will need to show that they understand and have mastered these techniques. A bank of downloadable data sets to compliment the tables provided in the textbook are provided free for you.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309465370 Total Pages :195 pages Book Rating :4.3/5 (94 download)
Book Synopsis Federal Statistics, Multiple Data Sources, and Privacy Protection by : National Academies of Sciences, Engineering, and Medicine
Download or read book Federal Statistics, Multiple Data Sources, and Privacy Protection written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-01-27 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.
Book Synopsis Statistical Methods for the Social Sciences by : Alan Agresti
Download or read book Statistical Methods for the Social Sciences written by Alan Agresti and published by . This book was released on 2013-07-30 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth edition has an even stronger emphasis on concepts and applications, with greater attention to "real data" both in the examples and exercises. The mathematics is still downplayed, in particular probability, which is all too often a stumbling block for students. On the other hand, the text is not a cookbook. Reliance on an overly simplistic recipe-based approach to statistics is not the route to good statistical practice. Changes in the Fourth Edition: Since the first edition, the increase in computer power coupled with the continued improvement and accessibility of statistical software has had a major impact on the way social scientists analyze data. Because of this, this book does not cover the traditional shortcut hand-computational formulas and approximations. The presentation of computationally complex methods, such as regression, emphasizes interpretation of software output rather than the formulas for performing the analysis. Teh text contains numerous sample printouts, mainly in the style of SPSS and occasionaly SAS, both in chapter text and homework problems. This edition also has an appendix explaining how to apply SPSS and SAS to conduct the methods of each chapter and a website giving links to information about other software.
Book Synopsis Statistical Methods for Social Scientists by : Eric A. Hanushek
Download or read book Statistical Methods for Social Scientists written by Eric A. Hanushek and published by Academic Press. This book was released on 2013-10-22 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aspects of this text which we believe are novel, at least in degree, include: an effort to motivate different sections with practical examples and an empirical orientation; an effort to intersperse several easily motivated examples throughout the book and to maintain some continuity in these examples; and the extensive use of Monte Carlo simulations to demonstrate particular aspects of the problems and estimators being considered. In terms of material being presented, the unique aspects include the first chapter which attempts to address the use of empirical methods in the social sciences, the seventh chapter which considers models with discrete dependent variables and unobserved variables. Clearly these last two topics in particular are quite advanced--more advanced than material that is currently available on the subject. These last two topics are also currently experiencing rapid development and are not adequately described in most other texts.
Book Synopsis Encyclopedia of Measurement and Statistics by : Neil J. Salkind
Download or read book Encyclopedia of Measurement and Statistics written by Neil J. Salkind and published by SAGE. This book was released on 2007 with total page 1417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description
Book Synopsis Statistics for the Social Sciences by : R. Mark Sirkin
Download or read book Statistics for the Social Sciences written by R. Mark Sirkin and published by SAGE Publications, Incorporated. This book was released on 1999-05-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do your students lack confidence in handling quantitative work? Do they get confused about how to enter statistical data on SAS and SPSS programs? This Second Edition of Mark Sirkin's popular textbook is the solution for these dilemmas. The book progresses from concepts that require little computational work to the more demanding. It emphasizes utilization so that students appreciate the usefulness of statistics and shows how the interpretation of data is related to the methods by which data was obtained. The author includes coverage of the scientific method, levels of measurement and the interpretation of tables.
Book Synopsis Statistical Analysis with Measurement Error or Misclassification by : Grace Y. Yi
Download or read book Statistical Analysis with Measurement Error or Misclassification written by Grace Y. Yi and published by Springer. This book was released on 2017-08-02 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems. Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods—such as likelihood and estimating function theory—or modeling schemes in varying settings—such as survival analysis and longitudinal data analysis—can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods. This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data. Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute.
