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Adjustment For Measurement Error In Multilevel Analysis
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Book Synopsis Adjustment for Measurement Error in Multilevel Analysis by : Geoffrey Michael Woodhouse
Download or read book Adjustment for Measurement Error in Multilevel Analysis written by Geoffrey Michael Woodhouse and published by . This book was released on 1998 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Measurement Error in Longitudinal Data by : Alexandru Cernat
Download or read book Measurement Error in Longitudinal Data written by Alexandru Cernat and published by Oxford University Press. This book was released on 2021-03-18 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Longitudinal data is essential for understanding how the world around us changes. Most theories in the social sciences and elsewhere have a focus on change, be it of individuals, of countries, of organizations, or of systems, and this is reflected in the myriad of longitudinal data that are being collected using large panel surveys. This type of data collection has been made easier in the age of Big Data and with the rise of social media. Yet our measurements of the world are often imperfect, and longitudinal data is vulnerable to measurement errors which can lead to flawed and misleading conclusions. Measurement Error in Longitudinal Data tackles the important issue of how to investigate change in the context of imperfect data. It compiles the latest advances in estimating change in the presence of measurement error from several fields and covers the entire process, from the best ways of collecting longitudinal data, to statistical models to estimate change under uncertainty, to examples of researchers applying these methods in the real world. This book introduces the essential issues of longitudinal data collection, such as memory effects, panel conditioning (or mere measurement effects), the use of administrative data, and the collection of multi-mode longitudinal data. It also presents some of the most important models used in this area, including quasi-simplex models, latent growth models, latent Markov chains, and equivalence/DIF testing. Finally, the use of vignettes in the context of longitudinal data and estimation methods for multilevel models of change in the presence of measurement error are also discussed.
Author :Anjali Mazumder Publisher :Library and Archives Canada = Bibliothèque et Archives Canada ISBN 13 :9780494021903 Total Pages :214 pages Book Rating :4.0/5 (219 download)
Book Synopsis Assessing the Impact of Measurement Error in Multilevel Models Via MCMC Methods [microform] by : Anjali Mazumder
Download or read book Assessing the Impact of Measurement Error in Multilevel Models Via MCMC Methods [microform] written by Anjali Mazumder and published by Library and Archives Canada = Bibliothèque et Archives Canada. This book was released on 2005 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this thesis is to integrate three areas of statistical research---multilevel modeling, Markov chain Monte Carlo (MCMC) methods, and measurement error. Three distinct types of multilevel models are considered: random-intercepts models, random-slopes models, and models with complex variation at level-1. These models are fitted using MCMC and maximum likelihood methods and the fits are compared. Finally, the effects of measurement error in predictors are assessed for different reliabilities and adjusted for using MCMC methods. The results indicate that MCMC samplers with non-informative priors produce similar results to maximum likelihood estimates and adjust for measurement error in predictors effectively. In general, MCMC methods give smaller standard errors, making inferential statements more powerful, and facilitate the use of additional information to guide the measurement and regression process. The simulations were performed using S-plus and the multilevel model problems were formulated and solved using MLwiN.
Book Synopsis Measurement Error by : John P. Buonaccorsi
Download or read book Measurement Error written by John P. Buonaccorsi and published by CRC Press. This book was released on 2010-03-02 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu
Book Synopsis Multilevel Analysis by : Tom A. B. Snijders
Download or read book Multilevel Analysis written by Tom A. B. Snijders and published by SAGE. This book was released on 1999 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.
Book Synopsis Measurement Error in Nonlinear Models by : Raymond J. Carroll
Download or read book Measurement Error in Nonlinear Models written by Raymond J. Carroll and published by CRC Press. This book was released on 1995-07-06 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides an up-to-date discussion of analysis strategies for regression problems in which predictor variables are measured with errors. The analysis of nonlinear regression models includes generalized linear models, transform-both-sides models and quasilikelihood and variance function problems. The text concentrates on the general ideas and strategies of estimation and inference rather than being concerned with a specific problem. Measurement error occurs in many fields, such as biometry, epidemiology and economics. In particular, the book contains a large number of epidemiological examples. An outline of strategies for handling progressively more difficult problems is also provided.
Book Synopsis Doing Meta-Analysis with R by : Mathias Harrer
Download or read book Doing Meta-Analysis with R written by Mathias Harrer and published by CRC Press. This book was released on 2021-09-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
Book Synopsis An Investigation Into the Effectiveness of Simulation-extrapolation for Correcting Measurement Error-induced Bias in Multilevel Models by : Christopher Custer
Download or read book An Investigation Into the Effectiveness of Simulation-extrapolation for Correcting Measurement Error-induced Bias in Multilevel Models written by Christopher Custer and published by . This book was released on 2015 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is an investigation into correcting the bias introduced by measurement errors into multilevel models. The proposed method for this correction is simulation-extrapolation (SIMEX). The paper begins with a detailed discussion of measurement error and its effects on parameter estimation. We then describe the simulation-extrapolation method and how it corrects for the bias introduced by the measurement error. Multilevel models and their corresponding parameters are also defined before performing a simulation. The simulation involves estimating the multilevel model parameters using our true explanatory variables, the observed measurement error variables, and two different SIMEX techniques. The estimates obtained from our true explanatory values were used as a baseline for comparing the effectiveness of the SIMEX method for correcting bias. From these results, we were able to determine that the SIMEX was very effective in correcting the bias in estimates of the fixed effects parameters and often provided estimates that were not significantly different than those from the estimates derived using the true explanatory variables. The simulation also suggested that the SIMEX approach was effective in correcting bias for the random slope variance estimates, but not for the random intercept variance estimates. Using the simulation results as a guideline, we then applied the SIMEX approach to an orthodontics dataset to illustrate the application of SIMEX to real data.
Book Synopsis Measurement Error in Nonlinear Models by : Raymond J. Carroll
Download or read book Measurement Error in Nonlinear Models written by Raymond J. Carroll and published by CRC Press. This book was released on 2006-06-21 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and ex
Book Synopsis Multilevel Statistical Models by : Harvey Goldstein
Download or read book Multilevel Statistical Models written by Harvey Goldstein and published by John Wiley & Sons. This book was released on 2011-07-08 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Throughout the social, medical and other sciences the importance of understanding complex hierarchical data structures is well understood. Multilevel modelling is now the accepted statistical technique for handling such data and is widely available in computer software packages. A thorough understanding of these techniques is therefore important for all those working in these areas. This new edition of Multilevel Statistical Models brings these techniques together, starting from basic ideas and illustrating how more complex models are derived. Bayesian methodology using MCMC has been extended along with new material on smoothing models, multivariate responses, missing data, latent normal transformations for discrete responses, structural equation modeling and survival models. Key Features: Provides a clear introduction and a comprehensive account of multilevel models. New methodological developments and applications are explored. Written by a leading expert in the field of multilevel methodology. Illustrated throughout with real-life examples, explaining theoretical concepts. This book is suitable as a comprehensive text for postgraduate courses, as well as a general reference guide. Applied statisticians in the social sciences, economics, biological and medical disciplines will find this book beneficial.
Book Synopsis Multilevel Modeling by : Steven P. Reise
Download or read book Multilevel Modeling written by Steven P. Reise and published by Psychology Press. This book was released on 2003-01-30 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book appeals to researchers who work with nested data structures or repeated measures data, including biomed & health researchers, clinical/intervention researchers and developmental & educational psychologists. Also some potential as a grad lvl tex
Book Synopsis Adjustment for Measurement Error by :
Download or read book Adjustment for Measurement Error written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A variety of complications arise when imperfect measurements, W, are observed in place of a true variable of interest, X. In the context of linear and non-linear regression models where X is a covariate, regression parameter estimators obtained when W is substituted for X may be substantially biased. Many strategies for correcting for measurement error depend on the specific modeling or regression context and can be intractable in highly non-linear models. In addition, previous methods often assume that the measurement error is normally distributed. In our work, we focus on re-creating the distribution of X from the observed W, either as the primary quantity of interest or as a means to improving parameter estimation. We obtain estimators of X for which the first M sample moments are unbiased for the corresponding moments of X. We investigate the benefit of substituting these estimates in density estimation, logistic regression and survival models. We compare this moment adjusted imputation (MAI) approach to existing alternatives in applications with normally distributed measurement error. We identify an important case of chi-square measurement error and propose a variety of methods to adjust for it, including a version of MAI. We find that MAI is often superior and has the advantage that once the estimates of X are obtained, they can be substituted in any model, including complicated non-linear models.
Book Synopsis Handbook of Multilevel Analysis by : Jan Deleeuw
Download or read book Handbook of Multilevel Analysis written by Jan Deleeuw and published by Springer Science & Business Media. This book was released on 2007-12-26 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the biomedical sciences. The chapter authors are all leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is essential for empirical researchers in these fields.
Book Synopsis Flexible Imputation of Missing Data, Second Edition by : Stef van Buuren
Download or read book Flexible Imputation of Missing Data, Second Edition written by Stef van Buuren and published by CRC Press. This book was released on 2018-07-17 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Correcting for Measurement Error and Misclassification Using General Location Models by : Muhire Honorine Kwizera
Download or read book Correcting for Measurement Error and Misclassification Using General Location Models written by Muhire Honorine Kwizera and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proposed method uses observed data from both the calibration and main study samples and incorporates relationships among all variables in measurement error adjustment, unlike existing methods that only use the calibration data for model estimation. We assume by strong nondifferential measurement error (sNDME) that the measurement error is independent of all the error-free variables given the true value of the error-prone variable. The sNDME assumption allows us to identify our model parameters. We show through simulations that the proposed method yields reduced bias, smaller mean squared error, and interval coverage closer to the nominal level compared to existing methods in regression settings. Furthermore, this improvement is pronounced with increased measurement error, higher correlation between covariates, and stronger covariate effects. We apply the new method to the New York City Neighborhood Asthma and Allergy Study to examine the association between indoor allergen concentrations and asthma morbidity among urban asthmatic children.
Book Synopsis An Introduction to Multilevel Modeling Techniques by : Ronald H. Heck
Download or read book An Introduction to Multilevel Modeling Techniques written by Ronald H. Heck and published by Psychology Press. This book was released on 1999-11-01 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad overview of basic multilevel modeling issues and illustrates techniques building analyses around several organizational data sets. Although the focus is primarily on educational and organizational settings, the examples will help the reader discover other applications for these techniques. Two basic classes of multilevel models are developed: multilevel regression models and multilevel models for covariance structures--are used to develop the rationale behind these models and provide an introduction to the design and analysis of research studies using two multilevel analytic techniques--hierarchical linear modeling and structural equation modeling.
Book Synopsis Measurement Error Models by : Wayne A. Fuller
Download or read book Measurement Error Models written by Wayne A. Fuller and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "The effort of Professor Fuller is commendable . . . [the book] provides a complete treatment of an important and frequently ignored topic. Those who work with measurement error models will find it valuable. It is the fundamental book on the subject, and statisticians will benefit from adding this book to their collection or to university or departmental libraries." -Biometrics "Given the large and diverse literature on measurement error/errors-in-variables problems, Fuller's book is most welcome. Anyone with an interest in the subject should certainly have this book." -Journal of the American Statistical Association "The author is to be commended for providing a complete presentation of a very important topic. Statisticians working with measurement error problems will benefit from adding this book to their collection." -Technometrics " . . . this book is a remarkable achievement and the product of impressive top-grade scholarly work." -Journal of Applied Econometrics Measurement Error Models offers coverage of estimation for situations where the model variables are observed subject to measurement error. Regression models are included with errors in the variables, latent variable models, and factor models. Results from several areas of application are discussed, including recent results for nonlinear models and for models with unequal variances. The estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals are addressed, and in addition, procedures are illustrated with data drawn from nearly twenty real data sets.