Generalized Multiple Indicators Multiple Causes Measurement Error Models

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Generalized Multiple Indicators, Multiple Causes Measurement Error Models

Author : Carmen Tekwe
Publisher :
ISBN 13 :
Total Pages : 285 pages
Book Rating : 4.:/5 (724 download)

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Book Synopsis Generalized Multiple Indicators, Multiple Causes Measurement Error Models by : Carmen Tekwe

Download or read book Generalized Multiple Indicators, Multiple Causes Measurement Error Models written by Carmen Tekwe and published by . This book was released on 2011 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Indicators, Multiple Causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times however when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error.^The objectives of this dissertation are: (1) to extend the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model, (2) to extend the classical linear MIMIC models to allow both Berkson and classical measurement errors where the distributions of the manifest variables belong in the exponential family, defining the generalized linear MIMIC ME (G-MIMIC ME) model, (3) to develop likelihood based estimation methods using the EM algorithm with Monte Carlo approximation to the integral in the E-step for both the MIMIC ME and G-MIMIC ME models, and (4) to obtain data driven estimates of the variance of the classical measurement error associated with log(DS02), an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure. Participants of the Adult Health Study (AHS) cohort of the atomic bomb data who were exposed to radiation emitted from the detonation of the bombs^with complete data were studied. The defined MIMIC ME model was applied to study the effects of dyslipidemia, a latent construct and the effect of true radiation dose on the physical manifestations of dyslipidemia (triglycerides, bad cholesterol and HDL cholesterol). The G-MIMIC ME model is also applied to study the effect of genetic damage (a latent construct based on exposure to atomic bomb radiation) and the effect of true radiation dose on the physical manifestations of genetic damage (chromosome aberrations (CA) and the amount of hemizygous mutant fractions at the glycopherin A locus in red mature blood cells (GPA)). We find that radiation dose was positively related to triglycerides (p-value

Multiple Indicators, Multiple Causes Measurement Error Models

Author :
Publisher :
ISBN 13 :
Total Pages : 13 pages
Book Rating : 4.:/5 (982 download)

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Book Synopsis Multiple Indicators, Multiple Causes Measurement Error Models by :

Download or read book Multiple Indicators, Multiple Causes Measurement Error Models written by and published by . This book was released on 2014 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple indicators, multiple causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times, however, when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this study are as follows: (i) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model; (ii) to develop likelihood-based estimation methods for the MIMIC ME model; and (iii) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. Finally, as a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure.

Measurement Error Models

Author : Wayne A. Fuller
Publisher : John Wiley & Sons
ISBN 13 : 0470317337
Total Pages : 474 pages
Book Rating : 4.4/5 (73 download)

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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.

Multiple Indicators

Author : John L. Sullivan
Publisher : SAGE
ISBN 13 : 9780803913691
Total Pages : 92 pages
Book Rating : 4.9/5 (136 download)

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Book Synopsis Multiple Indicators by : John L. Sullivan

Download or read book Multiple Indicators written by John L. Sullivan and published by SAGE. This book was released on 1979 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAGE provides a presentation and critique of the use of multiple measures of theoretical concepts for the assessment of validity (using the multi-trait multi-method matrix) and reliability (using multiple indicators with a path analytic framework).

Measurement Error and Latent Variables in Econometrics

Author : T. Wansbeek
Publisher : North Holland
ISBN 13 :
Total Pages : 464 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Measurement Error and Latent Variables in Econometrics by : T. Wansbeek

Download or read book Measurement Error and Latent Variables in Econometrics written by T. Wansbeek and published by North Holland. This book was released on 2000-12-08 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book first discusses in depth various aspects of the well-known inconsistency that arises when explanatory variables in a linear regression model are measured with error. Despite this inconsistency, the region where the true regression coeffecients lies can sometimes be characterized in a useful way, especially when bounds are known on the measurement error variance but also when such information is absent. Wage discrimination with imperfect productivity measurement is discussed as an important special case. Next, it is shown that the inconsistency is not accidental but fundamental. Due to an identification problem, no consistent estimators may exist at all. Additional information is desirable. This information can be of various types. One type is exact prior knowledge about functions of the parameters. This leads to the CALS estimator. Another major type is in the form of instrumental variables. Many aspects of this are discussed, including heteroskedasticity, combination of data from different sources, construction of instruments from the available data, and the LIML estimator, which is especially relevant when the instruments are weak. The scope is then widened to an embedding of the regression equation with measurement error in a multiple equations setting, leading to the exploratory factor analysis (EFA) model. This marks the step from measurement error to latent variables. Estimation of the EFA model leads to an eigenvalue problem. A variety of models is reviewed that involve eignevalue problems as their common characteristic. EFA is extended to confirmatory factor analysis (CFA) by including restrictions on the parameters of the factor analysis model, and next by relating the factors to background variables. These models are all structural equation models (SEMs), a very general and important class of models, with the LISREL model as its best-known representation, encompassing almost all linear equation systems with latent variables. Estimation of SEMs can be viewed as an application of the generalized method of moments (GMM). GMM in general and for SEM in particular is discussed at great length, including the generality of GMM, optimal weighting, conditional moments, continuous updating, simulation estimation, the link with the method of maximum likelihood, and in particular testing and model evaluation for GMM. The discussion concludes with nonlinear models. The emphasis is on polynomial models and models that are nonlinear due to a filter on the dependent variables, like discrete choice models or models with ordered categorical variables.

Measurement Error in Nonlinear Models

Author : Raymond J. Carroll
Publisher : CRC Press
ISBN 13 : 9780412047213
Total Pages : 334 pages
Book Rating : 4.0/5 (472 download)

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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.

Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable

Author : Karl G. Jöreskog
Publisher :
ISBN 13 :
Total Pages : 9 pages
Book Rating : 4.:/5 (254 download)

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Book Synopsis Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable by : Karl G. Jöreskog

Download or read book Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable written by Karl G. Jöreskog and published by . This book was released on 1975 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Measurement Error in Nonlinear Models

Author : Raymond J. Carroll
Publisher : CRC Press
ISBN 13 : 1420010131
Total Pages : 484 pages
Book Rating : 4.4/5 (2 download)

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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

Statistical Analysis of Measurement Error Models and Applications

Author : Philip J. Brown
Publisher : American Mathematical Soc.
ISBN 13 : 0821851179
Total Pages : 262 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Statistical Analysis of Measurement Error Models and Applications by : Philip J. Brown

Download or read book Statistical Analysis of Measurement Error Models and Applications written by Philip J. Brown and published by American Mathematical Soc.. This book was released on 1990 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measurement error models describe functional relationships among variables observed, subject to random errors of measurement. This book treats general aspects of the measurement problem and features a discussion of the history of measurement error models.

Two Aspects of Measurement Error Models

Author : Yonghong (Fred) Yang
Publisher :
ISBN 13 :
Total Pages : 266 pages
Book Rating : 4.:/5 (89 download)

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Book Synopsis Two Aspects of Measurement Error Models by : Yonghong (Fred) Yang

Download or read book Two Aspects of Measurement Error Models written by Yonghong (Fred) Yang and published by . This book was released on 1996 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Measurement Error

Author : John P. Buonaccorsi
Publisher : CRC Press
ISBN 13 : 1420066587
Total Pages : 465 pages
Book Rating : 4.4/5 (2 download)

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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

Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable

Author : Karl Gustav Jöreskog
Publisher :
ISBN 13 :
Total Pages : 33 pages
Book Rating : 4.:/5 (7 download)

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Book Synopsis Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable by : Karl Gustav Jöreskog

Download or read book Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable written by Karl Gustav Jöreskog and published by . This book was released on 1973 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Generalized Latent Variable Modeling

Author : Anders Skrondal
Publisher : CRC Press
ISBN 13 : 1135443408
Total Pages : 523 pages
Book Rating : 4.1/5 (354 download)

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Book Synopsis Generalized Latent Variable Modeling by : Anders Skrondal

Download or read book Generalized Latent Variable Modeling written by Anders Skrondal and published by CRC Press. This book was released on 2004-05-11 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and statistics. They present exciting and realistic applications that demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology. The examples considered include many nonstandard response types, such as ordinal, nominal, count, and survival data. Joint modeling of mixed responses, such as survival and longitudinal data, is also illustrated. Numerous displays, figures, and graphs make the text vivid and easy to read. About the authors: Anders Skrondal is Professor and Chair in Social Statistics, Department of Statistics, London School of Economics, UK Sophia Rabe-Hesketh is a Professor of Educational Statistics at the Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA.

Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Multiple Indicators and Multiple Causes (MIMIC) Models as a Mixed-Modelling Technique

Author : Clay Posey
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Multiple Indicators and Multiple Causes (MIMIC) Models as a Mixed-Modelling Technique by : Clay Posey

Download or read book Multiple Indicators and Multiple Causes (MIMIC) Models as a Mixed-Modelling Technique written by Clay Posey and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Formative modelling of latent constructs has produced great interest and discussion among scholars in recent years. However, confusion exists surrounding the ability of researchers to validate these models especially with covariance-based structural equation modelling (CB-SEM) techniques. This manuscript helps to clarify these issues and explains how formatively modelled constructs can be assessed rigorously by researchers using CB-SEM capabilities. In particular, we explain and provide an applied example of a mixed-modelling technique termed multiple indicators and multiple causes (MIMIC) models. Using this approach, researchers can assess formatively modelled constructs as the final, distal dependent variable in structural models, which modelling is traditionally impossible due to the mathematical identification rules of CB-SEM. Moreover, we assert that researchers can use MIMIC models to assess the content validity of a set of formative indicators quantitatively -- something considered conventionally only from a qualitative standpoint. Our research example used in this manuscript involving protection-motivated behaviors (PMBs) details the entire process of MIMIC modelling and provides a set of detailed guidelines for researchers to follow when developing new constructs modelled as MIMIC structures.

The Multiple Indicator, Multiple Cause Model with Several Latent Variables

Author : Johannes Ledolter
Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (253 download)

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Book Synopsis The Multiple Indicator, Multiple Cause Model with Several Latent Variables by : Johannes Ledolter

Download or read book The Multiple Indicator, Multiple Cause Model with Several Latent Variables written by Johannes Ledolter and published by . This book was released on 1976 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Companion to Theoretical Econometrics

Author : Badi H. Baltagi
Publisher : John Wiley & Sons
ISBN 13 : 047099830X
Total Pages : 736 pages
Book Rating : 4.4/5 (79 download)

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Book Synopsis A Companion to Theoretical Econometrics by : Badi H. Baltagi

Download or read book A Companion to Theoretical Econometrics written by Badi H. Baltagi and published by John Wiley & Sons. This book was released on 2008-04-15 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Companion to Theoretical Econometrics provides a comprehensive reference to the basics of econometrics. This companion focuses on the foundations of the field and at the same time integrates popular topics often encountered by practitioners. The chapters are written by international experts and provide up-to-date research in areas not usually covered by standard econometric texts. Focuses on the foundations of econometrics. Integrates real-world topics encountered by professionals and practitioners. Draws on up-to-date research in areas not covered by standard econometrics texts. Organized to provide clear, accessible information and point to further readings.