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Book
1 online resource (747 pages).
  • 1 Improving Surveys with Paradata: Introduction 1 Frauke Kreuter 1.1 Introduction 1 1.2 Paradata and Metadata 3 1.3 Auxiliary Data and Paradata 4 1.4 Paradata in the Total Survey Error Framework 4 1.5 Paradata in Survey Production 5 1.6 Special Challenges in the Collection and Use of Paradata 7 1.7 Future of Paradata 8 PART I PARADATA AND SURVEY ERRORS 2 Paradata for Nonresponse Error Investigation 3 Frauke Kreuter and Kristen Olson 2.1 Introduction 3 2.2 Sources of Paradata 4 2.3 Nonresponse Rates and Nonresponse Bias 10 2.4 Paradata and Responsive Designs 20 2.5 Paradata and Nonresponse Adjustment 21 2.6 Issues in Practice 22 2.7 Summary and Take Home Messages 24 3 Collecting Paradata for Measurement Error Evaluations 33 Kristen Olson and Bryan Parkhurst 3.1 Introduction 33 3.2 Paradata and Measurement Error 34 3.3 Types of paradata 38 3.4 Differences in Paradata by Modes 45 3.5 Turning paradata into data sets 51 3.6 Summary 55 4 Analyzing Paradata to Investigate Measurement Error 63 Ting Yan and Kristen Olson 4.1 Introduction 63 4.2 Review of Empirical Literature on the Use of Paradata for Measurement Error Investigation 64 4.3 Analyzing paradata 66 4.4 Four empirical examples 73 4.5 Cautions 81 4.6 Concluding Remarks 82 5 Paradata for Coverage Research 89 Stephanie Eckman 5.1 Introduction 89 5.2 Housing Unit Frames 93 5.3 Telephone Number Frames 101 5.4 Household Rosters 103 5.5 Population Registers 105 5.6 Subpopulation Frames 106 5.7 Web Surveys 106 5.8 Conclusion 107 PART II PARADATA IN SURVEY PRODUCTION 6 Design and Management Strategies for Paradata-Driven Responsive Design 117 Nicole G. Kirgis and James M. Lepkowski 6.1 Introduction 117 6.2 From Repeated Cross-Section to Continuous Design 118 6.3 Paradata Design 123 6.4 Key Design Change 1: A New Employment Model 128 6.5 Key Design Change 2: Field Efficient Sample Design 130 6.6 Key Design Change 3: Replicate Sample Design 131 6.7 Key Design Change 4: Responsive Design Sampling of Nonrespondents in a Second Phase 132 6.8 Key Design Change 5: Active Responsive Design Interventions 134 6.9 Concluding Remarks 135 7 Using Paradata-Driven Models to Improve Contact Rates 141 James Wagner 7.1 Introduction 141 7.2 Background 142 7.3 The Survey Setting 144 7.4 Experiments: Data and Methods 145 7.5 Experiments: Results 157 7.6 Discussion 162 8 Using Paradata to Study Response to Within-Survey Requests 169 Joseph W. Sakshaug 8.1 Introduction 169 8.2 Consent to Link Survey and Administrative Records 173 8.3 Consent to Collect Biomeasures in Population-Based Surveys 177 8.4 Switching Data Collection Modes 179 8.5 Income Item Nonresponse and Quality of Income Reports 181 8.6 Summary 185 9 Managing Data Quality Indicators with Paradata-Based Statistical Quality Control Tools 191 Matt Jans, Robyn Sirkis and David Morgan 9.1 Introduction 191 9.2 Defining and Choosing Key Performance Indicators (KPIs) 193 9.3 KPI Displays and the Enduring Insight of Walter Shewhart 201 9.4 Implementation Steps for Survey Analytic Quality Control with Paradata Control Charts 212 9.5 A Method for Improving Measurement Process Quality Indicators 214 9.6 Reections on SPC, Visual Data Displays, and Challenges to Quality Control 221 9.7 Some Advice on Using Charts 223 Appendix 225 10 Paradata as Input to Monitoring Representativeness and Measurement Profiles 233 Barry Schouten and Melania Calinescu 10.1 Introduction 233 10.2 Measurement profiles 235 10.3 Tools for monitoring nonresponse and measurement profiles 238 10.4 Monitoring and improving response: a demonstration using the LFS 243 10.5 Including paradata observations on households and persons 254 10.6 General discussion 256 10.7 Take home messages 257 PART III SPECIAL CHALLENGES 11 Paradata in Web Surveys 263 Mario Callegaro 11.1 Survey data types 263 11.2 Collection of paradata 264 11.3 Typology of paradata in web surveys 265 11.4 Using paradata to change the survey in real time: adaptive scripting 273 11.5 Paradata in online panels 274 11.6 Software to collect paradata 274 11.7 Analysis of paradata: levels of aggregation 275 11.8 Privacy and ethical issues in collecting web survey paradata 276 11.9 Summary and conclusions on paradata in web surveys 277 12 Modeling Call Record Data: Examples from Cross-Sectional and Longitudinal Surveys 283 Gabriele B. Durrant, Julia D'Arrigo and Gerrit Muller 12.1 Introduction 283 12.2 Call record data 285 12.3 Modeling approaches 287 12.4 Illustration of call record data analysis using two example datasets 294 12.5 Summary 305 13 Bayesian Penalized Spline Models for Statistical Process Monitoring of Survey Paradata Quality Indicators 311 Joseph L. Schafer 13.1 Introduction 311 13.2 Overview of splines 316 13.3 Penalized splines as linear mixed models 323 13.4 Bayesian methods 327 13.5 Extensions 330 14 The Quality of Paradata: A Literature Review 341 Brady T. West and Jennifer Sinibaldi 14.1 Introduction 341 14.2 Existing Studies Examining the Quality of Paradata 342 14.3 Possible Mechanisms Leading to Error in Paradata 354 14.4 Take Home Messages 357 15 The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study 363 Brady T. West 15.1 Introduction 363 15.2 Design of Simulation Studies 367 15.3 Simulation Results 372 15.4 Take Home Messages 386 15.5 Future Research 388 Topic Index 393.
  • (source: Nielsen Book Data)9780470905418 20160711
Explore the practices and cutting-edge research on the new and exciting topic of paradata Paradata are measurements related to the process of collecting survey data. Improving Surveys with Paradata: Analytic Uses of Process Information is the most accessible and comprehensive contribution to this up-and-coming area in survey methodology. Featuring contributions from leading experts in the field, Improving Surveys with Paradata: Analytic Uses of Process Information introduces and reviews issues involved in the collection and analysis of paradata. The book presents readers with an overview of the indispensable techniques and new, innovative research on improving survey quality and total survey error. Along with several case studies, topics include: * Using paradata to monitor fieldwork activity in face-to-face, telephone, and web surveys * Guiding intervention decisions during data collection * Analysis of measurement, nonresponse, and coverage error via paradata Providing a practical, encompassing guide to the subject of paradata, the book is aimed at both producers and users of survey data. Improving Surveys with Paradata: Analytic Uses of Process The book also serves as an excellent resource for courses on data collection, survey methodology, and nonresponse and measurement error.
(source: Nielsen Book Data)9780470905418 20160711
Book
xi, 212 p. : ill. ; 24 cm
Green Library
Book
xiii, 198 p. : ill. ; 25 cm.
  • The Position of Statistical Methods in Social Research Introduction The Use of Statistical Methods in Social Research Cases and Variables The Logic of Sampling Estimating and Measuring One Important Thing Studying the Relationship between Two Variables Linear Regression Models and Their Generalizations Time Matters Statistical Case-Oriented Methods Methods for Analyzing Latent Variables Causal Analysis.
  • (source: Nielsen Book Data)9781847872876 20160604
"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.
(source: Nielsen Book Data)9781847872876 20160604
Green Library
Book
xvi, 810 pages : illustrations ; 24 cm
  • The Theory of Probability: Probability on Abstract Sets-- Probability on Sets of Real Numbers-- Mathematical Expectation-- Models for Distributions-- The Theory of Statistics: Sampling Distributions-- Asymptotic Distribution Theory-- Estimation-- Tests of Parametric Hypotheses-- Tests of Nonparametric Hypotheses-- A Survey of Bayesian Methods-- Modeling Relatedness: Regression Analysis.
  • (source: Nielsen Book Data)9789814513159 20160612
This book develops the theory of probability and mathematical statistics at a level suitable for those at the frontiers of applied research, and it provides the necessary concepts of measure theory and analysis along the way. Down-to-earth explanations and an abundance of examples and exercises throughout the text make these concepts accessible to those with preparation limited to vector calculus and elementary statistics. Complete, detailed solutions to all the exercises are at the end of each chapter. These both develop one's technique for problem solving and afford immediate self-assessment of the level of understanding. The book is in two parts. Part I, The Theory of Probability, begins with elementary set theory, proceeds through basic measure and probability on abstract spaces, to random variables and probability on sets of real numbers, to integration and mathematical expectation, and concludes with a survey of models for distributions of random variables. Part II, The Theory of Statistics, begins with sampling theory and distribution theory for statistics from normal populations, proceeds to asymptotic (large-sample) theory, and on to point and interval estimation and tests of parametric hypotheses. The three concluding chapters cover tests of nonparametric hypotheses (with emphasis on goodness of fit), Bayesian methods, and linear and nonlinear regression. Researchers and graduate students in such applied fields as actuarial science, biostatistics, economics, finance, mathematical psychology, and systems engineering will find this book to be a valuable learning tool and, thereafter, an essential reference.
(source: Nielsen Book Data)9789814513159 20160612
Green Library
Book
xxiii, 716 pages : illustrations ; 26 cm
  • Part I: Basic Principles1. Introduction - Yang-chih Fu, Dominique Joye, Tom W. Smith and Christof Wolf2. Survey standards - Tom W. Smith 3. Total survey error: a paradigm for survey methodology - Lars E. Lyberg and Herbert F. Weisberg 4. Challenges of comparative survey research - Timothy P. Johnson and Michael Braun Part II: Surveys and Societies5. Surveys and society - Claire Durand 6. Defining and assessing survey climate - Geert Loosveldt and Dominique Joye 7. The Ethical issues of survey and market research - Kathy Joe, Finn Raben and Adam Phillips8. Observations on the historical development of polling - Kathleen A. Frankovic Part III: Planning a Survey9. Research question and designs for survey research - Ben Jann and Thomas Hinz 10. Total survey error paradigm: : Theory and Practice - Paul P. Biemer 11. Survey mode or survey modes? - Edith de Leeuw and Jernej Berzelak 12. Surveying in multi-cultural and multi-national contexts - Beth-Ellen Pennell and Kristen Cibelli-Hibben 13. Surveys in societies in turmoil - Zeina N. Mneimneh, Beth-Ellen Pennell, Jennifer Kelley and Kristen Cibelli-Hibben Part IV: Measurement14. What does Measurement Mean in a Survey Context? - Jaak Billiet 15. Cognitive models of answering processes - Kristen Miller and Gordon B. Willis16. Designing questions and questionnaires - Jolene D. Smyth 17. Creating a good question: how to use cumulative experience - Melanie Revilla, Diana Zavala-Rojas and Willem Saris18. Designing a mixed-mode survey - Don A. Dillman and Michelle L. Edwards 19. The Translation of Measurement Instruments for Cross-cultural Surveys - Dorothee Behr and Kuniaki Shishido 20. When Translation is not Enough: Background Variables in Comparative Surveys - Silke Schneider, Dominique Joye and Christof WolfPart V: Sampling21. Basics of sampling for survey research - Yves Tille and Alina Matei22. Nonprobability sampling - Vasja Vehovar, Vera Toepoel and Stephanie Steinmetz23. Special challenges of sampling for comparative surveys - Siegfried Gabler and Sabine Hader Part VI: Data Collection24. Questionnaire pretesting - Gordon B. Willis 25. Survey fieldwork - Annelies G. Blom 26. Responsive and adaptive designs - Francois Laflamme and James Wagner 27. Unit nonresponse - Ineke A. L. Stoop 28. Incentives as a possible measure to increase response rates - Michele Ernst Stahli and Dominique Joye Part VII: Preparing Data for Use29. Documenting Survey Data Across the Life Cycle - Mary Vardigan, Peter Granda and Lynette Hoelter30. Weighting: principles and practicalities - Pierre Lavallee and Jean-Francois Beaumont 31. Analysis of data from stratified and clustered surveys - Stephanie Eckman and Brady T. West 32. Analytical Potential Versus Data Confidentiality - Finding the Optimal Balance - Heike Wirth 33. Harmonizing Survey Questions Between Cultures and Over Time - Christof Wolf, Silke L. Schneider, Dorothee Behr and Dominique JoyePart VIII: Assessing and Improving Data Quality34. Survey data quality and measurement precision - Duane F. Alwin 35. Nonresponse error: detection and correction - Jelke Bethlehem and Barry Schouten 36. Response styles in surveys: understanding their causes and mitigating their impact - Caroline Roberts37. Dealing with missing values - Martin Spiess 38. Another Look at Survey Data Quality - Victor Thiessen and Jorg Blasius 39. Assessment of cross-cultural comparability - Jan Cieciuch, Eldad Davidov, Peter Schmidt and Rene AlgesheimerPart IX: Further Issues40. Data preservation, secondary analysis, and replication: learning from existing data - Lynette Hoelter, Amy Pienta and Jared Lyle41. Record linkage - Rainer Schnell 42. Supplementing cross-national surveys with contextual data - Jessica Fortin-Rittberger, David Howell, Stephen Quinlan and Bojan Todosijevic43. The Globalization of surveys - Tom W. Smith and Yang-chih Fu.
  • (source: Nielsen Book Data)9781446282663 20170821
Survey Methodology is becoming a more structured field of research, deserving of more and more academic attention. The SAGE Handbook of Survey Methodology explores both the increasingly scientific endeavour of surveys and their growing complexity, as different data collection modes and information sources are combined. The handbook takes a global approach, with a team of international experts looking at local and national specificities, as well as problems of cross-national, comparative survey research. The chapters are organized into seven major sections, each of which represents a stage in the survey life-cycle: Surveys and Societies Planning a Survey Measurement Sampling Data Collection Preparing Data for Use Assessing and Improving Data Quality The SAGE Handbook of Survey Methodology is a landmark and essential tool for any scholar within the social sciences.
(source: Nielsen Book Data)9781446282663 20170821
Law Library (Crown)
Book
1 online resource (1 volume)
  • Preface xvii Financial Glossary xxii Part I Measure Theory 1 Sets and Sequences 3 2 Measures 15 3 Extension of Measures 29 4 Lebesgue-Stieltjes Measures 37 5 Measurable Functions 47 6 Lebesgue Integration 57 7 The Radon-Nikodym Theorem 77 8 LP Spaces 85 9 Convergence 97 10 Product Measures 113 Part II Probability Theory 11 Events and Random Variables 127 12 Independence 141 13 Expectation 161 14 Conditional Expectation 173 15 Inequalities 189 16 Law of Large Numbers 199 17 Characteristic Functions 217 18 Discrete Distributions 227 19 Continuous Distributions 239 20 Central Limit Theorems 257 Part III Stochastic Processes 21 Stochastic Processes 271 22 Martingales 291 23 Stopping Times 301 24 Martingale Inequalities 321 25 Martingale Convergence Theorems 333 26 Random Walks 343 27 Poisson Processes 357 28 Brownian Motion 373 29 Markov Processes 389 30 Levy Processes 401 Part IV Stochastic Calculus 31 The Wiener Integral 421 32 The Ito Integral 431 33 Extension of the Ito Integral 453 34 Martingale Stochastic Integrals 463 35 The Ito Formula 477 36 Martingale Representation Theorem 495 37 Change of Measure 503 38 Stochastic Differential Equations 515 39 Diffusion 531 40 The Feynman-Kac Formula 547 Part V Stochastic Financial Models 41 Discrete-Time Models 561 42 Black-Scholes Option Pricing Models 579 43 Path-Dependent Options 593 44 American Options 609 45 Short Rate Models 629 46 Instantaneous Forward Rate Models 647 47 LIBOR Market Models 667 References 687 List of Symbols 703 Subject Index 707.
  • (source: Nielsen Book Data)9781118831960 20160711
An introduction to the mathematical theory and financial models developed and used on Wall Street Providing both a theoretical and practical approach to the underlying mathematical theory behind financial models, Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach presents important concepts and results in measure theory, probability theory, stochastic processes, and stochastic calculus. Measure theory is indispensable to the rigorous development of probability theory and is also necessary to properly address martingale measures, the change of numeraire theory, and LIBOR market models. In addition, probability theory is presented to facilitate the development of stochastic processes, including martingales and Brownian motions, while stochastic processes and stochastic calculus are discussed to model asset prices and develop derivative pricing models. The authors promote a problem-solving approach when applying mathematics in real-world situations, and readers are encouraged to address theorems and problems with mathematical rigor. In addition, Measure, Probability, and Mathematical Finance features: * A comprehensive list of concepts and theorems from measure theory, probability theory, stochastic processes, and stochastic calculus * Over 500 problems with hints and select solutions to reinforce basic concepts and important theorems * Classic derivative pricing models in mathematical finance that have been developed and published since the seminal work of Black and Scholes Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach is an ideal textbook for introductory quantitative courses in business, economics, and mathematical finance at the upper-undergraduate and graduate levels. The book is also a useful reference for readers who need to build their mathematical skills in order to better understand the mathematical theory of derivative pricing models.
(source: Nielsen Book Data)9781118831960 20160711
Book
x, 210 p. : ill. ; 26 cm.
  • 1. Statistical modelling: an overview 2. Research designs and data 3. Statistical preliminaries 4. Multiple regression for continuous response variables 5. Logistic regression for binary response variables 6. Multinomial logistic regression for multinomial response variables 7. Loglinear modelling 8. Ordinal logistic regression for ordered categorical response variables 9. Multilevel modelling 10. Latent variables and factor analysis 11. Causal modelling: simultaneous equation and structural equation models 12. Longitudinal data analysis 13. Event history models.
  • (source: Nielsen Book Data)9780415448406 20160528
This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers.Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-linear models, multilevel models, latent variable models (factor analysis), path analysis and simultaneous equation models and models for longitudinal data and event histories. An accompanying website hosts the datasets and further exercises in order that the reader may practice developing statistical models. It is an ideal tool for postgraduate social science students, research students and practicing social researchers in universities, market research, government social research and the voluntary sector.
(source: Nielsen Book Data)9780415448406 20160528
Green Library

8. Survey methodology [2009]

Book
xxi, 461 p. : ill., maps ; 26 cm.
  • An introduction to survey methodology
  • Inference and error in surveys
  • Target populations, sampling frames, and coverage error
  • Sample design and sampling error
  • Methods of data collection
  • Nonresponse in sample surveys
  • Questions and answers in surveys
  • Evaluating survey questions
  • Survey interviewing
  • Postcollection processing of survey data
  • Principles and practices related to ethical research
  • FAQs about survey methodology.
Praise for the First Edition : "The book makes a valuable contribution by synthesizing current research and identifying areas for future investigation for each aspect of the survey process." - Journal of the American Statistical Association "Overall, the high quality of the text material is matched by the quality of writing ..." - Public Opinion Quarterly "...it should find an audience everywhere surveys are being conducted." - Technometrics This new edition of Survey Methodology continues to provide a state-of-the-science presentation of essential survey methodology topics and techniques. The volume's six world-renowned authors have updated this Second Edition to present newly emerging approaches to survey research and provide more comprehensive coverage of the major considerations in designing and conducting a sample survey. Key topics in survey methodology are clearly explained in the book's chapters, with coverage including sampling frame evaluation, sample design, development of questionnaires, evaluation of questions, alternative modes of data collection, interviewing, nonresponse, post-collection processing of survey data, and practices for maintaining scientific integrity. Acknowledging the growing advances in research and technology, the Second Edition features: Updated explanations of sampling frame issues for mobile telephone and web surveys New scientific insight on the relationship between nonresponse rates and nonresponse errors Restructured discussion of ethical issues in survey research, emphasizing the growing research results on privacy, informed consent, and confidentiality issues The latest research findings on effective questionnaire development techniques The addition of 50# more exercises at the end of each chapter, illustrating basic principles of survey design An expanded FAQ chapter that addresses the concerns that accompany newly established methods Providing valuable and informative perspectives on the most modern methods in the field, Survey Methodology , Second Edition is an ideal book for survey research courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing survey methodologists and any professional who employs survey research methods.
(source: Nielsen Book Data)9780470465462 20160608
Law Library (Crown)
Book
1 online resource (xxi, 461 pages) : ill.
  • PREFACE TO THE FIRST EDITION xv PREFACE TO THE SECOND EDITION xix ACKNOWLEDGEMENTS xxi CHAPTER 1. AN INTRODUCTION TO SURVEY METHODOLOGY 1.1 Introduction 2 1.2 A Brief History of Survey Research 3 1.3 Some Examples of Ongoing Surveys 7 1.4 What is Survey Methodology? 30 1.5 The Challenge of Survey Methodology 32 1.6 About this Book 34 CHAPTER 2. INFERENCE AND ERROR IN SURVEYS 2.1 Introduction 39 2.2 The Lifecycle of a Survey From a Design Perspective 41 2.3 The Lifecycle of a Survey from A Quality Perspective 49 2.4 Putting It All Together 60 2.5 Error Notions in Different Kinds of Statistics 61 2.6 Nonstatistical Notions of Survey Quality 62 2.7 Summary 63 CHAPTER 3. TARGET POPULATIONS, SAMPLING FRAMES, AND COVERAGE ERROR 3.1 Introduction 69 3.2 Populations and Frames 69 3.3 Coverage Properties of Sampling Frames 72 3.4 Alternative Frames for the Target Population of Households or Persons 81 3.5 Frame Issues for Other Common Target Populations 84 3.6 Coverage Error 87 3.7 Reducing Undercoverage 88 3.8 Summary 94 CHAPTER 4. SAMPLE DESIGN AND SAMPLING ERROR 4.1 Introduction 97 4.2 Samples and Estimates 99 4.3 Simple Random Sampling 103 4.4 Cluster Sampling 106 4.5 Stratification and Stratified Sampling 113 4.6 Systematic Selection 123 4.7 Complications in Practice 125 4.8 Sampling US Telephone Households 133 4.9 Selecting Persons Within Households 136 4.10 Summary 138 CHAPTER 5. METHODS OF DATA COLLECTION 5.1 Alternative Methods of Data Collection 150 5.2 Choosing the Appropriate Method 159 5.3 Effects of Different Data Collection Methods on Survey Errors 160 5.4 Using Multiple Modes of Data Collection 175 5.5 Summary 177 CHAPTER 6. NONRESPONSE IN SAMPLE SURVEYS 6.1 Introduction 183 6.2 Response Rates 183 6.3 Impact of Nonresponse on the Quality of Survey Estimates 189 6.4 Thinking Causally About Survey Nonresponse Error 191 6.5 Dissecting the Nonresponse Phenomenon 192 6.6 Design Features to Reduce Unit Nonresponse 201 6.7 Item Nonresponse 208 6.8 Are Nonresponse Propensities Related to Other Error Sources? 210 6.9 Summary 210 CHAPTER 7. QUESTIONS AND ANSWERS IN SURVEYS 7.1 Alternatives Methods of Survey Measurement 217 7.2 Cognitive Processes in Answering Questions 218 7.3 Problems in Answering Survey Questions 225 7.4 Guidelines for Writing Good Questions 242 7.5 Summary 252 CHAPTER 8. EVALUATING SURVEY QUESTIONS 8.1 Introduction 259 8.2 Expert Reviews 260 8.3 Focus Groups 261 8.4 Cognitive Interviews 263 8.5 Field Pretests and Behavior Coding 265 8.6 Randomized or Split-Ballot Experiments 267 8.7 Applying Question Standards 268 8.8 Summary of Question Evaluation Tools 269 8.9 Linking Concepts of Measurement Quality to Statistical Estimates 274 8.10 Summary 286 CHAPTER 9. SURVEY INTERVIEWING 9.1 The Role of the Interviewer 291 9.2 Interviewer Bias 292 9.3 Interviewer Variance 295 9.4 Strategies for Reducing Interviewer Bias 300 9.5 Strategies for Reducing Interviewer-Related Variance 302 9.6 The Controversy About Standardized Interviewing 312 9.7 Interviewer Management 315 9.8 Validating the Work of Interviewers 319 9.9 The Use of Recorded Voices (and Faces) in Data Collection 322 9.10 Summary 323 CHAPTER 10. POSTCOLLECTION PROCESSING OF SURVEY DATA 10.1 Introduction 329 10.2 Coding 331 10.3 Entering Numeric Data into Files 344 10.4 Editing 345 10.5 Weighting 347 10.6 Imputation for Item-missing data 354 10.7 Sampling Variance Estimation for Complex Samples 359 10.8 Survey Data Documentation and Metadata 363 10.9 Summary 365 CHAPTER 11. PRINCIPLES AND PRACTICES RELATED TO ETHICAL RESEARCH 11.1 Introduction 371 11.2 Standards for the Conduct of Research 371 11.3 Standards for Dealing with Clients 374 11.4 Standards for Dealing with the Public 375 11.5 Standards for Dealing with Respondents 376 11.6 Emerging Ethical Issues 384 11.7 Research About Ethical Issues in Surveys 384 11.8 Administrative and Technical Procedures for Safe-Guarding Confidentiality 392 11.9 Summary and Conclusions 398 Keywords For More In-Depth Reading Exercises CHAPTER 12. FAQS ABOUT SURVEY METHODOLOGY 12.1 Introduction 405 12.2 The Questions and Their Answers 405 REFERENCES 421 INDEX 451.
  • (source: Nielsen Book Data)9780470465462 20160608
Praise for the First Edition : "The book makes a valuable contribution by synthesizing current research and identifying areas for future investigation for each aspect of the survey process." - Journal of the American Statistical Association "Overall, the high quality of the text material is matched by the quality of writing ..." - Public Opinion Quarterly "...it should find an audience everywhere surveys are being conducted." - Technometrics This new edition of Survey Methodology continues to provide a state-of-the-science presentation of essential survey methodology topics and techniques. The volume's six world-renowned authors have updated this Second Edition to present newly emerging approaches to survey research and provide more comprehensive coverage of the major considerations in designing and conducting a sample survey. Key topics in survey methodology are clearly explained in the book's chapters, with coverage including sampling frame evaluation, sample design, development of questionnaires, evaluation of questions, alternative modes of data collection, interviewing, nonresponse, post-collection processing of survey data, and practices for maintaining scientific integrity. Acknowledging the growing advances in research and technology, the Second Edition features: Updated explanations of sampling frame issues for mobile telephone and web surveys New scientific insight on the relationship between nonresponse rates and nonresponse errors Restructured discussion of ethical issues in survey research, emphasizing the growing research results on privacy, informed consent, and confidentiality issues The latest research findings on effective questionnaire development techniques The addition of 50# more exercises at the end of each chapter, illustrating basic principles of survey design An expanded FAQ chapter that addresses the concerns that accompany newly established methods Providing valuable and informative perspectives on the most modern methods in the field, Survey Methodology , Second Edition is an ideal book for survey research courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing survey methodologists and any professional who employs survey research methods.
(source: Nielsen Book Data)9780470465462 20160608
ebrary Access limited to 3 simultaneous users.

10. Survey methodology [2004]

Book
xix, 424 p. : ill. ; 26 cm.
  • Preface. Acknowledgements. Chapter 1. An Introduction to Survey Methodology. Chapter 2. Inference and Error in Surveys. Chapter 3. Target Populations, Sampling Frames, and Coverage Error. Chapter 4. Sample Design and Sampling Error. Chapter 5. Methods of Data Collection. Chapter 6. Nonresponse in Sample Surveys. Chapter 7. Questions and Answers in Surveys. Chapter 8. Evaluating Survey Questions. Chapter 9. Survey Interviewing. Chapter 10. Postcollection Processing of Survey Data. Chapter 11. Principles and Practices Related to Scientific Integrity. Chapter 12. FAQs About Survey Methodology. References. Index.
  • (source: Nielsen Book Data)9780471483489 20160528
This is an accessible introduction to the science and application of sample surveys. Over the past two decades, survey research has evolved significantly. "Survey Methodology" describes the basic principles of survey design discovered in methodological research over recent years and offers guidance for making successful decisions in the design and execution of high quality surveys. Written by six nationally recognized experts in the field, this book covers the major considerations in designing and conducting a sample survey. Topical, accessible, and succinct, this book represents the state of the science in survey methodology. Employing the "total survey error" paradigm as an organizing framework, it merges the science of surveys with state-of-the-art practices. End-of-chapter terms, references, and exercises enhance its value as a reference for practitioners and as a text for advanced students.
(source: Nielsen Book Data)9780471483489 20160528
Green Library
Book
xxi, 370 p. : ill. ; 24 cm.
  • General Introduction: M. Greenacre, Correspondence Analysis and its Interpretation. J. Blasius, Correspondence Analysis in Social Science Research. J. Blasius and M. Greenacre, Computation of Correspondence Analysis. P.G.M. van der Heijden, A. Mooijaart, and Y. Takane, Correspondence Analysis and Contingency Table Models. U. Bickenholt and Y. Takane, Linear Constraints in Correspondence Analysis. The BMS (K.M. van Meter, M.-A. Schiltz, P. Cibois, and L. Mounier), Correspondence Analysis: A History and French Sociological Perspective. Generalizations to Multivariate Data: M. Greenacre, Multiple and Joint Correspondence Analysis. L. Lebart, Complementary Use of Correspondence Analysis and Cluster Analysis. W.J. Heiser and J.J. Meulman, Homogeneity Analysis: Exploring the Distribution of Variables and their Nonlinear Relationships. J. Rovan, Visualizing Solutions in more than Two Dimensions. Analysis of Longitudinal Data: B. Martens, Analyzing Event History Data by Cluster Analysis and Multiple Correspondence Analysis: An example using data about work and occupations of scientists and engineers. V. Thiessen, H. Rohlinger, and J. Blasius, The Significance of Minor Changes in Panel Data: A correspondence analysis of the division of household tasks. T. Muller-Schneider, The Visualization of Structural Change by Means of Correspondence Analysis. Further Applications of Correspondence Analysis in Social Science Research: H. Giegler and H. Klein, Correspondence Analysis of Textual Data from Personal Advertisements. U. Wuggenig and P. Mnich, Explorations in Social Spaces: Gender, Age, Class Fractions and Photographical Choices of Objects. H.M.J.J. (Dirk) Snelders and M.J.W. Stokmans, Product Perception and Preference in Consumer Decision-making. References. Index.
  • (source: Nielsen Book Data)9780121045708 20160528
Correspondence Analysis in the Social Sciences gives a comprehensive description of this method of data visualization as well as numerous applications to a wide range of social science data. Various theoretical aspects are presented in a language accessible to both social scientists and statisticians and a wide variety of applications are given which demonstrate the versatility of the method to interpret tabular data in a unique graphical way.
(source: Nielsen Book Data)9780121045708 20160528
Green Library
Book
2 v. : ill. ; 24 cm.
  • General Problems and Issues. Structuring Change. Indices.
  • (source: Nielsen Book Data)9780127249605 20160528
  • J.A. Burr, J.R. Nesselroade, M.J. Rovine, M. Delaney, and P.A. Games, General Problems and Issues. J. Tisak, W. Meredith, J.J. McArdle, M.S. Aber, and P. Wood, Structuring Change. Author Index. Subject Index.
  • (source: Nielsen Book Data)9780127249629 20160528
  • T. Petersen, D. Thissen, R.D. Bock, R.J. Larsen, B. Schmitz, J. Tisak, and W. Meredith, Analysis of Time Series. C.C. Clogg, S.R. Eliason, J. Grego, D. Rindskopf, E. Erdfelder, K.A. Szabat, and A. von Eye, Analysis of Categorical Longitudinal Data. Author Index. Subject Index.
  • (source: Nielsen Book Data)9780127249636 20160528
These edited volumes present new statistical methods in a way that bridges the gap between theoretical and applied statistics. The volumes cover general problems and issues and more specific topics concerning the structuring of change, the analysis of time series, and the analysis of categorical longitudinal data. The book targets students of development and change in a variety of fields - psychology, sociology, anthropology, education, medicine, psychiatry, economics, behavioural sciences, developmental psychology, ecology, plant physiology, and biometry - with basic training in statistics and computing.
(source: Nielsen Book Data)9780127249636 20160528
Green Library
Book
171 p. : ill. ; 23 cm.
'Wright has written a very readable overview of the major quantitative techniques used in the social sciences. Her book covers many of the major techniques used in contemporary social science concisely and clearly and, therefore, should be useful to both practitioners and students alike.' -- George W Bohrnstedt, Indiana University.
(source: Nielsen Book Data)9780803912953 20160528
Green Library, SAL3 (off-campus storage)
Book
xvi, 356 pages : illustrations ; 25 cm
  • Research and statistics
  • Introduction to Stata
  • Simple (bivariate) regression
  • Multiple regression
  • Dummy-variable regression
  • Interaction/moderation effects using regression
  • Linear regression assumptions and diagnostics
  • Logistic regression
  • Multilevel analysis
  • Panel data analysis
  • Exploratory factor analysis
  • Structural equation modelling and confirmatory factor analysis
  • Critical issues.
Clear, intuitive and written with the social science student in mind, this book represents the ideal combination of statistical theory and practice. It focuses on questions that can be answered using statistics and addresses common themes and problems in a straightforward, easy-to-follow manner. The book carefully combines the conceptual aspects of statistics with detailed technical advice providing both the 'why' of statistics and the 'how'. Built upon a variety of engaging examples from across the social sciences it provides a rich collection of statistical methods and models. Students are encouraged to see the impact of theory whilst simultaneously learning how to manipulate software to meet their needs. The book also provides: * Original case studies and data sets * Practical guidance on how to run and test models in Stata * Downloadable Stata programmes created to work alongside chapters * A wide range of detailed applications using Stata * Step-by-step notes on writing the relevant code. This excellent text will give anyone doing statistical research in the social sciences the theoretical, technical and applied knowledge needed to succeed.
(source: Nielsen Book Data)9781473913233 20170424
Law Library (Crown)
Book
450 pages : illustrations ; 24 cm
SAL3 (off-campus storage)
Book
x, 357 pages : illustrations ; 24 cm
  • 1. Is Ours a Hard Science (And Do We Care)? 2. Cross-Level Direct Effects: Having Our Cake and Eating It Too? 3. Use of "Independent" Measures Does Not Solve the Shared Method Bias Problem 4. Size Matters ...Just Not in the Way You Think: Sample Size Requirements for Different Analyses 5. Practical Implications of Tests for Measurement Invariance: How important? 6. Missing Data Bias in Correlation Matrices: When is Pairwise Deletion a 'good enough' Missing Data Technique? 7. Separating Myth from Reality in Qualitative Research 8. Weight a Minute...What You See is Not What You Get! 9. The Reliability of Job Performance Ratings Equals 0.52 (NOT!) 10. Two Waves of Measurement do not a Longitudinal Study Make 11. Debunking Myths and Urban Legends about How to Identify Outliers 12. Pulling the Sobel Test Up By Its Bootstraps 13. Publication Bias: Understanding the Myths Around a Threat to Evidence Based Practice 14. Negatively-Worded Items Negatively Impact Survey Research 15. The Problem of Generational Change: Why Cross-Sectional Designs are Inadequate for Investigating Generational Differences 16. Justifying Aggregation: The Fallacy of the Wrong Level Revisited.
  • (source: Nielsen Book Data)9780415838993 20160618
This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are based partially in sound scientific rationale and partially in unfounded lore. Some examples of these "methodological urban legends" are characterized by manuscript critiques such as: (a) "your self-report measures suffer from common method bias"; (b) "your item-to-subject ratios are too low"; (c) "you can't generalize these findings to the real world"; or (d) "your effect sizes are too low." What do these critiques mean, and what is their historical basis? More Statistical and Methodological Myths and Urban Legends catalogs several of these quirky practices and outlines proper research techniques. Topics covered include sample size requirements, missing data bias in correlation matrices, negative wording in survey research, and much more.
(source: Nielsen Book Data)9780415838993 20160618
Green Library
Book
xxii, 392 p. : ill.
  • 1 Improving Surveys with Paradata: Introduction 1 Frauke Kreuter 1.1 Introduction 1 1.2 Paradata and Metadata 3 1.3 Auxiliary Data and Paradata 4 1.4 Paradata in the Total Survey Error Framework 4 1.5 Paradata in Survey Production 5 1.6 Special Challenges in the Collection and Use of Paradata 7 1.7 Future of Paradata 8 PART I PARADATA AND SURVEY ERRORS 2 Paradata for Nonresponse Error Investigation 3 Frauke Kreuter and Kristen Olson 2.1 Introduction 3 2.2 Sources of Paradata 4 2.3 Nonresponse Rates and Nonresponse Bias 10 2.4 Paradata and Responsive Designs 20 2.5 Paradata and Nonresponse Adjustment 21 2.6 Issues in Practice 22 2.7 Summary and Take Home Messages 24 3 Collecting Paradata for Measurement Error Evaluations 33 Kristen Olson and Bryan Parkhurst 3.1 Introduction 33 3.2 Paradata and Measurement Error 34 3.3 Types of paradata 38 3.4 Differences in Paradata by Modes 45 3.5 Turning paradata into data sets 51 3.6 Summary 55 4 Analyzing Paradata to Investigate Measurement Error 63 Ting Yan and Kristen Olson 4.1 Introduction 63 4.2 Review of Empirical Literature on the Use of Paradata for Measurement Error Investigation 64 4.3 Analyzing paradata 66 4.4 Four empirical examples 73 4.5 Cautions 81 4.6 Concluding Remarks 82 5 Paradata for Coverage Research 89 Stephanie Eckman 5.1 Introduction 89 5.2 Housing Unit Frames 93 5.3 Telephone Number Frames 101 5.4 Household Rosters 103 5.5 Population Registers 105 5.6 Subpopulation Frames 106 5.7 Web Surveys 106 5.8 Conclusion 107 PART II PARADATA IN SURVEY PRODUCTION 6 Design and Management Strategies for Paradata-Driven Responsive Design 117 Nicole G. Kirgis and James M. Lepkowski 6.1 Introduction 117 6.2 From Repeated Cross-Section to Continuous Design 118 6.3 Paradata Design 123 6.4 Key Design Change 1: A New Employment Model 128 6.5 Key Design Change 2: Field Efficient Sample Design 130 6.6 Key Design Change 3: Replicate Sample Design 131 6.7 Key Design Change 4: Responsive Design Sampling of Nonrespondents in a Second Phase 132 6.8 Key Design Change 5: Active Responsive Design Interventions 134 6.9 Concluding Remarks 135 7 Using Paradata-Driven Models to Improve Contact Rates 141 James Wagner 7.1 Introduction 141 7.2 Background 142 7.3 The Survey Setting 144 7.4 Experiments: Data and Methods 145 7.5 Experiments: Results 157 7.6 Discussion 162 8 Using Paradata to Study Response to Within-Survey Requests 169 Joseph W. Sakshaug 8.1 Introduction 169 8.2 Consent to Link Survey and Administrative Records 173 8.3 Consent to Collect Biomeasures in Population-Based Surveys 177 8.4 Switching Data Collection Modes 179 8.5 Income Item Nonresponse and Quality of Income Reports 181 8.6 Summary 185 9 Managing Data Quality Indicators with Paradata-Based Statistical Quality Control Tools 191 Matt Jans, Robyn Sirkis and David Morgan 9.1 Introduction 191 9.2 Defining and Choosing Key Performance Indicators (KPIs) 193 9.3 KPI Displays and the Enduring Insight of Walter Shewhart 201 9.4 Implementation Steps for Survey Analytic Quality Control with Paradata Control Charts 212 9.5 A Method for Improving Measurement Process Quality Indicators 214 9.6 Reections on SPC, Visual Data Displays, and Challenges to Quality Control 221 9.7 Some Advice on Using Charts 223 Appendix 225 10 Paradata as Input to Monitoring Representativeness and Measurement Profiles 233 Barry Schouten and Melania Calinescu 10.1 Introduction 233 10.2 Measurement profiles 235 10.3 Tools for monitoring nonresponse and measurement profiles 238 10.4 Monitoring and improving response: a demonstration using the LFS 243 10.5 Including paradata observations on households and persons 254 10.6 General discussion 256 10.7 Take home messages 257 PART III SPECIAL CHALLENGES 11 Paradata in Web Surveys 263 Mario Callegaro 11.1 Survey data types 263 11.2 Collection of paradata 264 11.3 Typology of paradata in web surveys 265 11.4 Using paradata to change the survey in real time: adaptive scripting 273 11.5 Paradata in online panels 274 11.6 Software to collect paradata 274 11.7 Analysis of paradata: levels of aggregation 275 11.8 Privacy and ethical issues in collecting web survey paradata 276 11.9 Summary and conclusions on paradata in web surveys 277 12 Modeling Call Record Data: Examples from Cross-Sectional and Longitudinal Surveys 283 Gabriele B. Durrant, Julia D'Arrigo and Gerrit Muller 12.1 Introduction 283 12.2 Call record data 285 12.3 Modeling approaches 287 12.4 Illustration of call record data analysis using two example datasets 294 12.5 Summary 305 13 Bayesian Penalized Spline Models for Statistical Process Monitoring of Survey Paradata Quality Indicators 311 Joseph L. Schafer 13.1 Introduction 311 13.2 Overview of splines 316 13.3 Penalized splines as linear mixed models 323 13.4 Bayesian methods 327 13.5 Extensions 330 14 The Quality of Paradata: A Literature Review 341 Brady T. West and Jennifer Sinibaldi 14.1 Introduction 341 14.2 Existing Studies Examining the Quality of Paradata 342 14.3 Possible Mechanisms Leading to Error in Paradata 354 14.4 Take Home Messages 357 15 The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study 363 Brady T. West 15.1 Introduction 363 15.2 Design of Simulation Studies 367 15.3 Simulation Results 372 15.4 Take Home Messages 386 15.5 Future Research 388 Topic Index 393.
  • (source: Nielsen Book Data)9780470905418 20160711
Explore the practices and cutting-edge research on the new and exciting topic of paradata Paradata are measurements related to the process of collecting survey data. Improving Surveys with Paradata: Analytic Uses of Process Information is the most accessible and comprehensive contribution to this up-and-coming area in survey methodology. Featuring contributions from leading experts in the field, Improving Surveys with Paradata: Analytic Uses of Process Information introduces and reviews issues involved in the collection and analysis of paradata. The book presents readers with an overview of the indispensable techniques and new, innovative research on improving survey quality and total survey error. Along with several case studies, topics include: * Using paradata to monitor fieldwork activity in face-to-face, telephone, and web surveys * Guiding intervention decisions during data collection * Analysis of measurement, nonresponse, and coverage error via paradata Providing a practical, encompassing guide to the subject of paradata, the book is aimed at both producers and users of survey data. Improving Surveys with Paradata: Analytic Uses of Process The book also serves as an excellent resource for courses on data collection, survey methodology, and nonresponse and measurement error.
(source: Nielsen Book Data)9780470905418 20160711
Book
1 online resource (1 v.) : ill.
  • 1 Improving Surveys with Paradata: Introduction 1 Frauke Kreuter 1.1 Introduction 1 1.2 Paradata and Metadata 3 1.3 Auxiliary Data and Paradata 4 1.4 Paradata in the Total Survey Error Framework 4 1.5 Paradata in Survey Production 5 1.6 Special Challenges in the Collection and Use of Paradata 7 1.7 Future of Paradata 8 PART I PARADATA AND SURVEY ERRORS 2 Paradata for Nonresponse Error Investigation 3 Frauke Kreuter and Kristen Olson 2.1 Introduction 3 2.2 Sources of Paradata 4 2.3 Nonresponse Rates and Nonresponse Bias 10 2.4 Paradata and Responsive Designs 20 2.5 Paradata and Nonresponse Adjustment 21 2.6 Issues in Practice 22 2.7 Summary and Take Home Messages 24 3 Collecting Paradata for Measurement Error Evaluations 33 Kristen Olson and Bryan Parkhurst 3.1 Introduction 33 3.2 Paradata and Measurement Error 34 3.3 Types of paradata 38 3.4 Differences in Paradata by Modes 45 3.5 Turning paradata into data sets 51 3.6 Summary 55 4 Analyzing Paradata to Investigate Measurement Error 63 Ting Yan and Kristen Olson 4.1 Introduction 63 4.2 Review of Empirical Literature on the Use of Paradata for Measurement Error Investigation 64 4.3 Analyzing paradata 66 4.4 Four empirical examples 73 4.5 Cautions 81 4.6 Concluding Remarks 82 5 Paradata for Coverage Research 89 Stephanie Eckman 5.1 Introduction 89 5.2 Housing Unit Frames 93 5.3 Telephone Number Frames 101 5.4 Household Rosters 103 5.5 Population Registers 105 5.6 Subpopulation Frames 106 5.7 Web Surveys 106 5.8 Conclusion 107 PART II PARADATA IN SURVEY PRODUCTION 6 Design and Management Strategies for Paradata-Driven Responsive Design 117 Nicole G. Kirgis and James M. Lepkowski 6.1 Introduction 117 6.2 From Repeated Cross-Section to Continuous Design 118 6.3 Paradata Design 123 6.4 Key Design Change 1: A New Employment Model 128 6.5 Key Design Change 2: Field Efficient Sample Design 130 6.6 Key Design Change 3: Replicate Sample Design 131 6.7 Key Design Change 4: Responsive Design Sampling of Nonrespondents in a Second Phase 132 6.8 Key Design Change 5: Active Responsive Design Interventions 134 6.9 Concluding Remarks 135 7 Using Paradata-Driven Models to Improve Contact Rates 141 James Wagner 7.1 Introduction 141 7.2 Background 142 7.3 The Survey Setting 144 7.4 Experiments: Data and Methods 145 7.5 Experiments: Results 157 7.6 Discussion 162 8 Using Paradata to Study Response to Within-Survey Requests 169 Joseph W. Sakshaug 8.1 Introduction 169 8.2 Consent to Link Survey and Administrative Records 173 8.3 Consent to Collect Biomeasures in Population-Based Surveys 177 8.4 Switching Data Collection Modes 179 8.5 Income Item Nonresponse and Quality of Income Reports 181 8.6 Summary 185 9 Managing Data Quality Indicators with Paradata-Based Statistical Quality Control Tools 191 Matt Jans, Robyn Sirkis and David Morgan 9.1 Introduction 191 9.2 Defining and Choosing Key Performance Indicators (KPIs) 193 9.3 KPI Displays and the Enduring Insight of Walter Shewhart 201 9.4 Implementation Steps for Survey Analytic Quality Control with Paradata Control Charts 212 9.5 A Method for Improving Measurement Process Quality Indicators 214 9.6 Reections on SPC, Visual Data Displays, and Challenges to Quality Control 221 9.7 Some Advice on Using Charts 223 Appendix 225 10 Paradata as Input to Monitoring Representativeness and Measurement Profiles 233 Barry Schouten and Melania Calinescu 10.1 Introduction 233 10.2 Measurement profiles 235 10.3 Tools for monitoring nonresponse and measurement profiles 238 10.4 Monitoring and improving response: a demonstration using the LFS 243 10.5 Including paradata observations on households and persons 254 10.6 General discussion 256 10.7 Take home messages 257 PART III SPECIAL CHALLENGES 11 Paradata in Web Surveys 263 Mario Callegaro 11.1 Survey data types 263 11.2 Collection of paradata 264 11.3 Typology of paradata in web surveys 265 11.4 Using paradata to change the survey in real time: adaptive scripting 273 11.5 Paradata in online panels 274 11.6 Software to collect paradata 274 11.7 Analysis of paradata: levels of aggregation 275 11.8 Privacy and ethical issues in collecting web survey paradata 276 11.9 Summary and conclusions on paradata in web surveys 277 12 Modeling Call Record Data: Examples from Cross-Sectional and Longitudinal Surveys 283 Gabriele B. Durrant, Julia D'Arrigo and Gerrit Muller 12.1 Introduction 283 12.2 Call record data 285 12.3 Modeling approaches 287 12.4 Illustration of call record data analysis using two example datasets 294 12.5 Summary 305 13 Bayesian Penalized Spline Models for Statistical Process Monitoring of Survey Paradata Quality Indicators 311 Joseph L. Schafer 13.1 Introduction 311 13.2 Overview of splines 316 13.3 Penalized splines as linear mixed models 323 13.4 Bayesian methods 327 13.5 Extensions 330 14 The Quality of Paradata: A Literature Review 341 Brady T. West and Jennifer Sinibaldi 14.1 Introduction 341 14.2 Existing Studies Examining the Quality of Paradata 342 14.3 Possible Mechanisms Leading to Error in Paradata 354 14.4 Take Home Messages 357 15 The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study 363 Brady T. West 15.1 Introduction 363 15.2 Design of Simulation Studies 367 15.3 Simulation Results 372 15.4 Take Home Messages 386 15.5 Future Research 388 Topic Index 393.
  • (source: Nielsen Book Data)9780470905418 20160711
Explore the practices and cutting-edge research on the new and exciting topic of paradata Paradata are measurements related to the process of collecting survey data. Improving Surveys with Paradata: Analytic Uses of Process Information is the most accessible and comprehensive contribution to this up-and-coming area in survey methodology. Featuring contributions from leading experts in the field, Improving Surveys with Paradata: Analytic Uses of Process Information introduces and reviews issues involved in the collection and analysis of paradata. The book presents readers with an overview of the indispensable techniques and new, innovative research on improving survey quality and total survey error. Along with several case studies, topics include: * Using paradata to monitor fieldwork activity in face-to-face, telephone, and web surveys * Guiding intervention decisions during data collection * Analysis of measurement, nonresponse, and coverage error via paradata Providing a practical, encompassing guide to the subject of paradata, the book is aimed at both producers and users of survey data. Improving Surveys with Paradata: Analytic Uses of Process The book also serves as an excellent resource for courses on data collection, survey methodology, and nonresponse and measurement error.
(source: Nielsen Book Data)9780470905418 20160711
Book
xviii, 330 p. : ill. ; 24 cm.
  • About the Authors. Preface. Introduction. CHAPTER 1: UNDERSTANDING RESEARCH. The Research Process. Types of Research. Research Proposals. Research Ethics. Getting Acquainted with SPSS. Summary. Key Terms. CHAPTER 2: THE WHO, HOW, AND WHY OF RESEARCH. Who: Selecting a Sample. How: Selecting a Research Strategy. Why: Doing Research That Makes a Difference. Summary. Key Terms. CHAPTER 3: QUANTITATIVE RESEARCH: MEASUREMENT AND DATA COLLECTION. Measurement: Turning Abstractions into Variables. Characteristics of Good Measures. Collecting Data. Summary. Key Terms. CHAPTER 4: QUANTITATIVE RESEARCH: DESCRIPTIVE AND CORRELATIONAL DESIGNS. Basic Concepts. Causation and Prediction. Data Gathering. Data Analysis. Summary. Key Terms. CHAPTER 5: QUANTITATIVE RESEARCH: BASIC EXPERIMENTAL DESIGNS. Experimental Validity. Types of Variables. Characteristics of Experiments. Types of Experimental Designs. Data Analysis. Summary. Key Terms. CHAPTER 6: QUANTITATIVE RESEARCH: ADVANCED EXPERIMENTAL DESIGNS. Basic Concepts. Repeated-Measures Designs. Complex Designs. Quasi-Experimental Designs. Data Analysis. Summary. Key Terms. CHAPTER 7: WHAT IS QUALITATIVE RESEARCH? Telling a Story ... Qualitatively. Two Worldviews on Research: Reality and Knowledge. Comparison of Quantitative and Qualitative Research. Critique of Quantitative Research. Crisis of Representation. Summary. Key Terms. CHAPTER 8: PLANNING YOUR QUALITATIVE STUDY: DESIGN, SAMPLING, AND DATA ANALYSIS. Designing Qualitative Research. Summary. Key Terms. CHAPTER 9: QUALITATIVE RESEARCH METHODS: ETHNOGRAPHY, PHENOMENOLOGY, CASE STUDY, TEXTUAL ANALYSIS, AND APPLIED RESEARCH. Ethnography. Phenomenology. Case Study. Textual Analysis. Applied Research Methods: Action and Evaluation Research. Summary. Key Terms. CHAPTER 10: QUALITATIVE RESEARCH TOOLS: INTERVIEWING, FOCUS GROUPS, AND OBSERVATION. The First Tool: Defi ning the Context. Qualitative Research Tools: How to Collect Data. Summary. Key Terms. CHAPTER 11: PRESENTING YOUR RESEARCH FINDINGS. Presenting Your Research with a Poster. Presenting Your Research in an Oral Presentation. Presenting Your Research in a Paper. Reducing Bias in Research Reporting. Summary. Key Terms. References. Appendix A: A Sample Manuscript from a Quantitative Study. Appendix B: A Sample Manuscript from a Qualitative Study. Glossary. Index.
  • (source: Nielsen Book Data)9780470343531 20160528
This book offers an innovative introduction to social research. The book explores all stages of the research process and it features both quantitative and qualitative methods. Research design topics include sampling techniques, choosing a research design, and determining research question that inform public opinion and direct future studies. Throughout the book, the authors provide vivid and engaging examples that reinforce the reading and understanding of social science research. 'Your Turn' boxes contain activities that allow students to practice research skills, such as sampling, naturalistic observation, survey collection, coding, analysis, and report writing.
(source: Nielsen Book Data)9780470343531 20160528
Green Library
Book
xix, 412 p. : ill. ; 24 cm.
  • Missing data techniques and low response rates : the role of systematic nonresponse parameters / Daniel A. Newman
  • The partial revival of a dead horse? : comparing classical test theory and item response theory / Michael J. Zickar, and Alison A. Broadfoot
  • Four common misconceptions in exploratory factor analysis / Deborah L. Bandalos and Meggen R. Boehm-Kaufman
  • Dr. StrangeLove, or : how I learned to stop worrying and love omitted variables / Adam W. Meade, Tara S. Behrend, and Charles E. Lance
  • The truth(s) on testing for mediation in the social and organizational sciences / James M. LeBreton, Jane Wu, and Mark N. Bing
  • Seven deadly myths of testing moderation in organizational research / Jeffrey R. Edwards
  • Alternative model specifications in structural equation modeling : facts, fictions, and truth / Robert J. Vandenberg and Darrin M. Grelle
  • On the practice of allowing correlated residuals among indicators in structural equation models / Ronald S. Landis, Bryan D. Edwards, and Jose M. Cortina
  • Qualitative research : the redheaded stepchild in organizational and social science research? / Lillian T. Eby, Carrie S. Hurst, and Marcus M. Butts
  • Do samples really matter that much? / Scott Highhouse and Jennifer Z. Gillespie
  • Sample size rules of thumb : evaluating three common practices / Herman Aguinis and Erika E. Harden
  • When small effect sizes tell a big story, and when large effect sizes don't / Jose M. Cortina and Ronald S. Landis
  • So why ask me? : are self-report data really that bad? / David Chan
  • If it ain't trait it must be method : (mis)application of the multitrait-multimethod design in organizational research / Charles E. Lance ... [et al.]
  • Chopped liver? OK. Chopped data? Not OK / Marcus M. Butts and Thomas W.H. Ng.
This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are sustained, in part, upon sound rationale and justification and, in part, upon unfounded lore. Some examples of these 'methodological urban legends' as we refer to them in this book are characterized by manuscript critiques such as: 'your self-report measures suffer from common method bias'; 'your item-to-subject ratios are too low'; 'you can't generalize these findings to the real world'; and, 'your effect sizes are too low'.Historically, there is a kernel of truth to most of these legends, but in many cases that truth has been long forgotten, ignored or embellished beyond recognition. This book examines several such legends. Each chapter is organized to address: what is the legend that 'we (almost) all know to be true'; what is the 'kernel of truth' to each legend; what are the myths that have developed around this kernel of truth; and, what should the state of the practice be. This book meets an important need for the accumulation and integration of these methodological and statistical practices.
(source: Nielsen Book Data)9780805862379 20160528
Green Library

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