Author: Guo-Liang Tian
Publisher: CRC Press
ISBN: 143985534X
Category : Mathematics
Languages : en
Pages : 316
Book Description
Respondents to survey questions involving sensitive information, such as sexual behavior, illegal drug usage, tax evasion, and income, may refuse to answer the questions or provide untruthful answers to protect their privacy. This creates a challenge in drawing valid inferences from potentially inaccurate data. Addressing this difficulty, non-rando
Incomplete Categorical Data Design
Author: Guo-Liang Tian
Publisher: CRC Press
ISBN: 143985534X
Category : Mathematics
Languages : en
Pages : 316
Book Description
Respondents to survey questions involving sensitive information, such as sexual behavior, illegal drug usage, tax evasion, and income, may refuse to answer the questions or provide untruthful answers to protect their privacy. This creates a challenge in drawing valid inferences from potentially inaccurate data. Addressing this difficulty, non-rando
Publisher: CRC Press
ISBN: 143985534X
Category : Mathematics
Languages : en
Pages : 316
Book Description
Respondents to survey questions involving sensitive information, such as sexual behavior, illegal drug usage, tax evasion, and income, may refuse to answer the questions or provide untruthful answers to protect their privacy. This creates a challenge in drawing valid inferences from potentially inaccurate data. Addressing this difficulty, non-rando
Flexible Imputation of Missing Data, Second Edition
Author: Stef van Buuren
Publisher: CRC Press
ISBN: 0429960352
Category : Mathematics
Languages : en
Pages : 444
Book Description
Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.
Publisher: CRC Press
ISBN: 0429960352
Category : Mathematics
Languages : en
Pages : 444
Book Description
Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.
Generalized Linear Models for Categorical and Continuous Limited Dependent Variables
Author: Michael Smithson
Publisher: CRC Press
ISBN: 1466551739
Category : Mathematics
Languages : en
Pages : 310
Book Description
Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. The book provides broad, but unified, coverage, and the authors integrate the concepts and ideas shared across models and types of data, especially regarding conceptual links between discrete and continuous limited dependent variables. The authors argue that these dependent variables are, if anything, more common throughout the human sciences than the kind that suit linear regression. They cover special cases or extensions of models, estimation methods, model diagnostics, and, of course, software. They also discuss bounded continuous variables, boundary-inflated models, and methods for modeling heteroscedasticity. Wherever possible, the authors have illustrated concepts, models, and techniques with real or realistic datasets and demonstrations in R and Stata, and each chapter includes several exercises at the end. The illustrations and exercises help readers build conceptual understanding and fluency in using these techniques. At several points the authors bring together material that has been previously scattered across the literature in journal articles, software package documentation files, and blogs. These features help students learn to choose the appropriate models for their purpose.
Publisher: CRC Press
ISBN: 1466551739
Category : Mathematics
Languages : en
Pages : 310
Book Description
Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. The book provides broad, but unified, coverage, and the authors integrate the concepts and ideas shared across models and types of data, especially regarding conceptual links between discrete and continuous limited dependent variables. The authors argue that these dependent variables are, if anything, more common throughout the human sciences than the kind that suit linear regression. They cover special cases or extensions of models, estimation methods, model diagnostics, and, of course, software. They also discuss bounded continuous variables, boundary-inflated models, and methods for modeling heteroscedasticity. Wherever possible, the authors have illustrated concepts, models, and techniques with real or realistic datasets and demonstrations in R and Stata, and each chapter includes several exercises at the end. The illustrations and exercises help readers build conceptual understanding and fluency in using these techniques. At several points the authors bring together material that has been previously scattered across the literature in journal articles, software package documentation files, and blogs. These features help students learn to choose the appropriate models for their purpose.
Handbook of Item Response Theory, Volume Two
Author: Wim J. van der Linden
Publisher: CRC Press
ISBN: 1498785689
Category : Mathematics
Languages : en
Pages : 487
Book Description
Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume Two: Statistical Tools presents classical and modern statistical tools used in item response theory (IRT). While IRT heavily depends on the use of statistical tools for handling its models and applications, systematic introductions and reviews that emphasize their relevance to IRT are hardly found in the statistical literature. This second volume in a three-volume set fills this void. Volume Two covers common probability distributions, the issue of models with both intentional and nuisance parameters, the use of information criteria, methods for dealing with missing data, and model identification issues. It also addresses recent developments in parameter estimation and model fit and comparison, such as Bayesian approaches, specifically Markov chain Monte Carlo (MCMC) methods.
Publisher: CRC Press
ISBN: 1498785689
Category : Mathematics
Languages : en
Pages : 487
Book Description
Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume Two: Statistical Tools presents classical and modern statistical tools used in item response theory (IRT). While IRT heavily depends on the use of statistical tools for handling its models and applications, systematic introductions and reviews that emphasize their relevance to IRT are hardly found in the statistical literature. This second volume in a three-volume set fills this void. Volume Two covers common probability distributions, the issue of models with both intentional and nuisance parameters, the use of information criteria, methods for dealing with missing data, and model identification issues. It also addresses recent developments in parameter estimation and model fit and comparison, such as Bayesian approaches, specifically Markov chain Monte Carlo (MCMC) methods.
Handbook of Item Response Theory
Author: Wim J. van der Linden
Publisher: CRC Press
ISBN: 1351645455
Category : Mathematics
Languages : en
Pages : 1584
Book Description
Drawing on the work of 75 internationally acclaimed experts in the field, Handbook of Item Response Theory, Three-Volume Set presents all major item response models, classical and modern statistical tools used in item response theory (IRT), and major areas of applications of IRT in educational and psychological testing, medical diagnosis of patient-reported outcomes, and marketing research. It also covers CRAN packages, WinBUGS, Bilog MG, Multilog, Parscale, IRTPRO, Mplus, GLLAMM, Latent Gold, and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton’s classic Handbook of Modern Item Response Theory, this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced, with uniform notation, format, and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT.
Publisher: CRC Press
ISBN: 1351645455
Category : Mathematics
Languages : en
Pages : 1584
Book Description
Drawing on the work of 75 internationally acclaimed experts in the field, Handbook of Item Response Theory, Three-Volume Set presents all major item response models, classical and modern statistical tools used in item response theory (IRT), and major areas of applications of IRT in educational and psychological testing, medical diagnosis of patient-reported outcomes, and marketing research. It also covers CRAN packages, WinBUGS, Bilog MG, Multilog, Parscale, IRTPRO, Mplus, GLLAMM, Latent Gold, and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton’s classic Handbook of Modern Item Response Theory, this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced, with uniform notation, format, and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT.
Improving Survey Methods
Author: Uwe Engel
Publisher: Routledge
ISBN: 131762971X
Category : Psychology
Languages : en
Pages : 452
Book Description
This state-of-the-art volume provides insight into the recent developments in survey research. It covers topics like: survey modes and response effects, bio indicators and paradata, interviewer and survey error, mixed-mode panels, sensitive questions, conducting web surveys and access panels, coping with non-response, and handling missing data. The authors are leading scientists in the field, and discuss the latest methods and challenges with respect to these topics. Each of the book’s eight parts starts with a brief chapter that provides an historical context along with an overview of today’s most critical survey methods. Chapters in the sections focus on research applications in practice and discuss results from field studies. As such, the book will help researchers design surveys according to today’s best practices. The book’s website www.survey-methodology.de provides additional information, statistical analyses, tables and figures. An indispensable reference for practicing researchers and methodologists or any professional who uses surveys in their work, this book also serves as a supplement for graduate or upper level-undergraduate courses on survey methods taught in psychology, sociology, education, economics, and business. Although the book focuses on European findings, all of the research is discussed with reference to the entire survey-methodology area, including the US. As such, the insights in this book will apply to surveys conducted around the world.
Publisher: Routledge
ISBN: 131762971X
Category : Psychology
Languages : en
Pages : 452
Book Description
This state-of-the-art volume provides insight into the recent developments in survey research. It covers topics like: survey modes and response effects, bio indicators and paradata, interviewer and survey error, mixed-mode panels, sensitive questions, conducting web surveys and access panels, coping with non-response, and handling missing data. The authors are leading scientists in the field, and discuss the latest methods and challenges with respect to these topics. Each of the book’s eight parts starts with a brief chapter that provides an historical context along with an overview of today’s most critical survey methods. Chapters in the sections focus on research applications in practice and discuss results from field studies. As such, the book will help researchers design surveys according to today’s best practices. The book’s website www.survey-methodology.de provides additional information, statistical analyses, tables and figures. An indispensable reference for practicing researchers and methodologists or any professional who uses surveys in their work, this book also serves as a supplement for graduate or upper level-undergraduate courses on survey methods taught in psychology, sociology, education, economics, and business. Although the book focuses on European findings, all of the research is discussed with reference to the entire survey-methodology area, including the US. As such, the insights in this book will apply to surveys conducted around the world.
Analysis of Integrated Data
Author: Li-Chun Zhang
Publisher: CRC Press
ISBN: 1498727999
Category : Mathematics
Languages : en
Pages : 273
Book Description
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.
Publisher: CRC Press
ISBN: 1498727999
Category : Mathematics
Languages : en
Pages : 273
Book Description
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.
Incomplete Categorical Data Design
Author: Guo-Liang Tian
Publisher: Chapman & Hall/CRC
ISBN: 9780367379629
Category : Sampling (Statistics)
Languages : en
Pages : 0
Book Description
A self-contained, systematic introduction, this book shows you how to draw valid statistical inferences from survey data with sensitive characteristics. It guides you in applying the non-randomized response approach in surveys and new non-randomized response designs. The techniques covered integrate the strengths of existing approaches, including randomized response models, incomplete categorical data design, the EM algorithm, the bootstrap method, and the data augmentation algorithm. All R codes for the examples are available online.
Publisher: Chapman & Hall/CRC
ISBN: 9780367379629
Category : Sampling (Statistics)
Languages : en
Pages : 0
Book Description
A self-contained, systematic introduction, this book shows you how to draw valid statistical inferences from survey data with sensitive characteristics. It guides you in applying the non-randomized response approach in surveys and new non-randomized response designs. The techniques covered integrate the strengths of existing approaches, including randomized response models, incomplete categorical data design, the EM algorithm, the bootstrap method, and the data augmentation algorithm. All R codes for the examples are available online.
Multilevel Modeling Using R
Author: W. Holmes Finch
Publisher: CRC Press
ISBN: 1466515864
Category : Mathematics
Languages : en
Pages : 225
Book Description
Multilevel Modelling using R provides a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. The book concludes with Bayesian fitting of multilevel models. Complete data sets for the book can be found on the book's website www.mlminr.com/
Publisher: CRC Press
ISBN: 1466515864
Category : Mathematics
Languages : en
Pages : 225
Book Description
Multilevel Modelling using R provides a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. The book concludes with Bayesian fitting of multilevel models. Complete data sets for the book can be found on the book's website www.mlminr.com/
Encyclopaedic Companion to Medical Statistics
Author: Brian S. Everitt
Publisher: John Wiley & Sons
ISBN: 1119957400
Category : Medical
Languages : en
Pages : 753
Book Description
Statistical methodology is of great importance to medical research and clinical practice. The Encyclopaedic Companion to Medical Statistics contains readable accounts of the key topics central to current research and practice. Each entry has been written by an individual chosen for both their expertise in the field and their ability to communicate statistical concepts successfully to medical researchers. Real examples from the biomedical literature and relevant illustrations feature in many entries and extensive cross–referencing signposts the reader to related entries. Key Features: Contains accounts of over 400 statistical topics central to current medical research. 80% of first edition entries updated and revised. Presents the latest techniques used at the cutting edge of medical research. Covers common errors in statistical analyses in medicine. Real examples from the biomedical literature and relevant illustrations feature throughout. Contains contributions from over 70 experts in the field. Medical researchers, researchers and practitioners in medical research and statistics will benefit greatly from this book.
Publisher: John Wiley & Sons
ISBN: 1119957400
Category : Medical
Languages : en
Pages : 753
Book Description
Statistical methodology is of great importance to medical research and clinical practice. The Encyclopaedic Companion to Medical Statistics contains readable accounts of the key topics central to current research and practice. Each entry has been written by an individual chosen for both their expertise in the field and their ability to communicate statistical concepts successfully to medical researchers. Real examples from the biomedical literature and relevant illustrations feature in many entries and extensive cross–referencing signposts the reader to related entries. Key Features: Contains accounts of over 400 statistical topics central to current medical research. 80% of first edition entries updated and revised. Presents the latest techniques used at the cutting edge of medical research. Covers common errors in statistical analyses in medicine. Real examples from the biomedical literature and relevant illustrations feature throughout. Contains contributions from over 70 experts in the field. Medical researchers, researchers and practitioners in medical research and statistics will benefit greatly from this book.