LEADER 06245nam 2200541Ia 450 001 9910830592103321 005 20180117165002.0 010 $a1-282-30772-X 010 $a9786612307720 010 $a0-470-31666-7 010 $a0-470-31733-7 035 $a(CKB)1000000000687540 035 $a(StDuBDS)AH3916609 035 $a(SSID)ssj0000340249 035 $a(PQKBManifestationID)11266901 035 $a(PQKBTitleCode)TC0000340249 035 $a(PQKBWorkID)10364954 035 $a(PQKB)10356474 035 $a(MiAaPQ)EBC469407 035 $a(PPN)15935580X 035 $a(EXLCZ)991000000000687540 100 $a19861110d1987 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMeasurement error models$b[electronic resource] /$fWayne A. Fuller 210 $aNew York $cWiley$dc1987 215 $a1 online resource (xxiii, 440 p. )$cillustrations 225 1 $aWiley series in probability and mathematical statistics. Probability and mathematical statistics,$x0271-6356 320 $aIncludes bibliography and indexes. 327 $aList of Examples. List of Principal Results. List of Figures. 1. A Single Explanatory Variable. 2. Vector Explanatory Variables. 3. Extensions of the Single Relation Model. 4. Multivariate Models. Bibliography. Author Index. Subject Index. 330 8 $aOffers coverage of estimation for situations where the model variables are observed subject to measurement error. This book includes regression models with errors in the variables, latent variable models, and factor models. It discusses results from areas of application, including results for nonlinear models and for models with unequal variances.$bThe 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. 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. 410 0$aWiley series in probability and mathematical statistics.$pProbability and mathematical statistics. 606 $aError analysis (Mathematics) 606 $aRegression analysis 615 0$aError analysis (Mathematics) 615 0$aRegression analysis. 676 $a511.43 700 $aFuller$b Wayne A$0116991 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830592103321 996 $aMeasurement error models$9197022 997 $aUNINA