Handbook of Measurement Error Models by Grace Y Yi
Reference text for statistical methods and applications for measurement error models for: researchers who work with error-contaminated data, graduate students from statistics and biostatistics, analysts in multiple fields, including medical research, biosciences, nutritional studies, epidemiological studies and environmental studies.-
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Handbook of Markov Chain Monte Carlo
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Handbook of Statistical Methods for Case-Control Studies
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Handbook of Meta-Analysis
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Handbook of Mixture Analysis
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Handbook of Graphical Models
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Handbook of Environmental and Ecological Statistics
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Handbook of Neuroimaging Data Analysis
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Handbook of Bayesian Variable Selection
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Handbook of Survival Analysis
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Handbook of Statistical Methods for Randomized Controlled Trials
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Handbook of Quantile Regression
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Handbook of Cluster Analysis
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Handbook of Design and Analysis of Experiments
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Handbook of Forensic Statistics
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Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials
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Handbook of Infectious Disease Data Analysis
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Handbook of Approximate Bayesian Computation
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Handbook of Spatial Statistics
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Handbook of Missing Data Methodology
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Handbook of Generalized Pairwise Comparisons
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Handbook of Sharing Confidential Data
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Handbook of Statistical Methods for Precision Medicine
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Handbook of Multiple Comparisons
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Handbook of Spatial Epidemiology
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Handbook of Discrete-Valued Time Series
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Handbook of Bayesian, Fiducial, and Frequentist Inference
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Longitudinal Data Analysis
"This handbook provides detailed and comprehensive developments and methods for meta-analysisIts insights and clear explanations make readers easily learn fundamental and advanced approaches to meta-analysis. This book is a valuable reference to develop new methods in meta-analysis and relevant materials provide motivating extensions in the future research."
- Biometrics
"Written by rigorous mathematical language, the papers in the book can be useful to professional statisticians and graduate students specializing in advanced regression modeling and analysis of data with measurement errors."
- Stan Lipovetsky in Technometrics, April 2023
Grace Y. Yi is Professor of Statistics at the University of Western Ontario where she holds a Tier I Canada Research Chair in Data Science. She is a Fellow of the Institute of Mathematical Statistics (IMS), a Fellow of the American Statistical Association (ASA), and an Elected Member of the International Statistical Institute (ISI). She authored the monograph Statistical Analysis with Measurement Error or Misclassification (2017, Springer).
Aurore Delaigle is Professor at the School of Mathematics and Statistics at the University of Melbourne. She is a Fellow of the Australian Academy of Science, a Fellow of the Institute of Mathematical Statistics (IMS), a Fellow of the American Statistical Association (ASA), and an Elected Member of the International Statistical Institute (ISI). She is a past recipient of the George W. Snedecor Award from the Committee of Presidents of Statistical Societies (COPSS) and of the Moran Medal from the Australian Academy of Science.
Paul Gustafson is Professor and Head of the Department of Statistics at the University of British Columbia. He is a Fellow of the American Statistical Association, the 2020 Gold Medalist of the Statistical Society of Canada, and the author of the monograph Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments (2004, Chapman and Hall, CRC Press).
| SKU | Unavailable |
| ISBN 13 | 9781138106406 |
| ISBN 10 | 1138106402 |
| Title | Handbook of Measurement Error Models |
| Author | Grace Y Yi |
| Series | Chapman And Hall Crc Handbooks Of Modern Statistical Methods |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2021-10-18 |
| Number of pages | 578 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |