LEADER 04604nam 22005775 450 001 9910254302603321 005 20250505001245.0 010 $a1-4939-6640-5 024 7 $a10.1007/978-1-4939-6640-0 035 $a(CKB)3710000001631044 035 $a(MiAaPQ)EBC4935684 035 $a(DE-He213)978-1-4939-6640-0 035 $a(PPN)203848128 035 $a(EXLCZ)993710000001631044 100 $a20170802d2017 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aStatistical Analysis with Measurement Error or Misclassification $eStrategy, Method and Application /$fby Grace Y. Yi 205 $a1st ed. 2017. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2017. 215 $a1 online resource (497 pages) 225 1 $aSpringer Series in Statistics,$x2197-568X 311 08$a1-4939-6638-3 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aInference Framework and Method -- Measurement Error and Misclassification: Introduction -- Survival Data with Measurement Error -- Recurrent Event Data with Measurement Error -- Longitudinal Data with Covariate Measurement Error -- Multi-State Models with Error-Prone Data -- Case-Control Studies with Measurement Error or Misclassification -- Analysis with Error in Responses -- Miscellaneous Topics -- Appendix -- References. . 330 $aThis monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems. Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods?such as likelihood and estimating function theory?or modeling schemes in varying settings?such as survival analysis and longitudinal data analysis?can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods. This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data. Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute. . 410 0$aSpringer Series in Statistics,$x2197-568X 606 $aStatistics 606 $aBiometry 606 $aEpidemiology 606 $aStatistical Theory and Methods 606 $aBiostatistics 606 $aEpidemiology 615 0$aStatistics. 615 0$aBiometry. 615 0$aEpidemiology. 615 14$aStatistical Theory and Methods. 615 24$aBiostatistics. 615 24$aEpidemiology. 676 $a511.43 700 $aYi$b Grace Y.$4aut$4http://id.loc.gov/vocabulary/relators/aut$0766751 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254302603321 996 $aStatistical analysis with measurement error or misclassification$91560439 997 $aUNINA