Details
Recent Advances on Sampling Methods and Educational Statistics
In Honor of S. Lynne StokesEmerging Topics in Statistics and Biostatistics
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171,19 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 25.11.2022 |
| ISBN/EAN: | 9783031145254 |
| Sprache: | englisch |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<p>This edited collection commemorates the career of Dr. S. Lynne Stokes by highlighting recent advances in her areas of research interest, emphasizing practical applications and future directions. It serves as a collective effort of leading statistical scientists who work at the cutting edge in statistical sampling.</p>
<p>S. Lynne Stokes is Professor of Statistical Science and Director of the Data Science Institute at Southern Methodist University, and Senior Fellow at the National Institute of Statistical Sciences. She has enjoyed a distinguished research career, making fundamental contributions to a variety of fields in statistical sampling. Reflecting on Professor Stokes' main areas of research, this volume is structured into three main parts:<br></p><p>I. ranked-set sampling, judgment post-stratified sampling, and capture-recapture methods </p>
<p>II. nonsampling errors in statistical sampling </p>
<p>III. educational and behavioral statistics.</p>
<p>This collection will be of interest to researchers, advanced students, and professionals in the public and private sectors who would like to learn more about latest advancements in statistical sampling, particularly those who work in educational and behavioral statistics.<br></p><br>
<p>S. Lynne Stokes is Professor of Statistical Science and Director of the Data Science Institute at Southern Methodist University, and Senior Fellow at the National Institute of Statistical Sciences. She has enjoyed a distinguished research career, making fundamental contributions to a variety of fields in statistical sampling. Reflecting on Professor Stokes' main areas of research, this volume is structured into three main parts:<br></p><p>I. ranked-set sampling, judgment post-stratified sampling, and capture-recapture methods </p>
<p>II. nonsampling errors in statistical sampling </p>
<p>III. educational and behavioral statistics.</p>
<p>This collection will be of interest to researchers, advanced students, and professionals in the public and private sectors who would like to learn more about latest advancements in statistical sampling, particularly those who work in educational and behavioral statistics.<br></p><br>
1. Predictive modelling and judgement post-stratification.- 2. Judgment post-stratified sampling: A comparison with ranked-set sampling.- 3. Efficient sample allocation by local adjustment for unbalanced ranked-set sampling.- 4. On the versatility of capture-recapture modeling: We can’t count what we don’t see.- 5. Advances in the use of capture-recapture methodology in the estimation of U.S. census coverage error.- 6. Measurement issues in synthesizing survey-item responses.- 7. Effects of two sources of nonsampling error in fishing surveys.- 8. Triple system estimation with erroneous enumerations.- 9. Record linkage in statistical sampling: Past, present, and future.- 10. A Bayesian latent variable model for analysis of empathic accuracy in psychology.- 11. Variance Estimation for Random-Groups Linking in Large-Scale Survey Assessments.- 12. Item Response Theory and Fisher Information for Small Tests.- 13. Statistical Evaluation of Process Variables: A Case Study on Writing Tool Usage in Educational Survey Assessment.<p></p> <br>
<b>Hon Keung Tony Ng </b>is a Professor with the Department of Mathematical Sciences, Bentley University, Waltham, MA, USA. Before joining Bentley University in July 2022, he was at Southern Methodist University for 20 years (2002-2022). He received the Ph.D. degree in mathematics from McMaster University, Hamilton, ON, Canada, in 2002. He is an associate editor of <i>Communications in Statistics</i>, <i>Computational Statistics</i>, <i>IEEE Transactions on Reliability</i>, <i>Journal of Statistical Computation and Simulation</i>, <i>Naval Research Logistics</i>, <i>Sequential Analysis</i>, and <i>Statistics and Probability Letters</i>. His research interests include reliability, censoring methodology, ordered data analysis, non-parametric methods, and statistical inference. He has published more than 150 research papers in refereed journals. He is the co-author of the book <i>Precedence-Type Tests and Applications</i> and co-editor of <i>Ordered Data Analysis, Modeling and Health Research Methods</i>; <i>Statistical Modeling for Degradation Data</i>; <i>Statistical Quality Technologies: Theory and Practice</i>; and <i>Bayesian Inference and Computation in Reliability and Survival Analysis</i>. Professor Ng is an elected senior member of IEEE (2008), an elected member of the International Statistical Institute (2008), and an elected fellow of the American Statistical Association (2016).<p><b>Daniel F. Heitjan </b>is Professor and Chair of Statistical Science at SMU and Professor of Population & Data Sciences at UT Southwestern Medical Center. A native of Detroit, he earned a BSc in Mathematics (1981), an MSc in Statistics (1984), and a PhD in Statistics (1985) from the University of Chicago. He served on the faculties of UCLA (1985–1988), Penn State (1988–1995), Columbia University (1995–2002), and the University of Pennsylvania (2002–2014) before moving to Texas in 2014. Dr. Heitjan has over 200 publications in the literature of medicine and statistics, and is an elected Fellow of the American Statistical Association (1997), the Institute of Mathematical Statistics (2012), and the Society for Clinical Trials (2017). He has served as Program Chair of the Joint Statistical Meetings (2005), Chair of the American Statistical Association’s Biometrics Section (2009), and President of the Eastern North American Region of the International Biometric Society (2013). His research interests include causal modeling, the theory of inference with incomplete data, and methods in clinical biostatistics.<br></p>
<p>This edited collection commemorates the career of Dr. S. Lynne Stokes by highlighting recent advances in her areas of research interest, emphasizing practical applications and future directions. It serves as a collective effort of leading statistical scientists who work at the cutting edge in statistical sampling.</p><p>S. Lynne Stokes is Professor of Statistical Science and Director of the Data Science Institute at Southern Methodist University, and Senior Fellow at the National Institute of Statistical Sciences. She has enjoyed a distinguished research career, making fundamental contributions to a variety of fields in statistical sampling. Reflecting on Professor Stokes' main areas of research, this volume is structured into three main parts:<br></p><p>I. ranked-set sampling, judgment post-stratified sampling, and capture-recapture methods </p><p>II. nonsampling errors in statistical sampling </p>III. educational and behavioral statistics<p></p><p>This collection will beof interest to researchers, advanced students, and professionals in the public and private sectors who would like to learn more about latest advancements in statistical sampling, particularly those who work in educational and behavioral statistics.</p>
Honors the contributions of Professor S. Lynne Stokes to theoretical and applied statistics Explores novel sampling methods and recent developments in statistical sampling Examines ranked-set sampling, judgment post-stratified sampling, and capture-recapture methods
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