Design of Observational Studies by Paul R Rosenbaum
This second edition of Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies.-
The Elements of Statistical Learning
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Dragons of Winter Night
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Functional Data Analysis
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Time Series: Theory and Methods
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Modeling Discrete Time-to-Event Data
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Targeted Learning
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Models for Discrete Longitudinal Data
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Regression Modeling Strategies
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Targeted Learning in Data Science
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An Introduction to Sequential Monte Carlo
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Sampling Algorithms
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Modern Multidimensional Scaling
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Correlation Theory of Stationary and Related Random Functions
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Mathematical Statistics
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Breakthroughs in Statistics
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Annotated Readings in the History of Statistics
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Statistical Models Based on Counting Processes
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Hidden Markov Processes and Adaptive Filtering
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Chaos: A Statistical Perspective
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A Comparison of the Bayesian and Frequentist Approaches to Estimation
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Smoothing Spline ANOVA Models
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Analysis of Neural Data
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Finite Mixture and Markov Switching Models
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The Gini Methodology
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Ten Projects in Applied Statistics
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Growth Curve Models and Statistical Diagnostics
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Statistical Methods in Software Engineering
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Markov Bases in Algebraic Statistics
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Data
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A Course on Point Processes
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Shrinkage Estimation
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Theory of Statistics
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Bayesian and Frequentist Regression Methods
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A Statistical Model
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Prediction Theory for Finite Populations
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Tools for Statistical Inference
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Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series
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ARMA Model Identification
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Statistical Design and Analysis for Intercropping Experiments
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Approximate Distributions of Order Statistics
“References are listed after each chapter … reflecting the wealth of his contribution to the subject of causal inference over the last four decades… The book is a comprehensive account of methods for comparing treatments in an observational study, rich with detailed illustrations using data for inferences of substance in education, epidemiology, economics and clinical medicine. … this is an absolute `must' for reading and reference for every statistician who works with observational studies … .” (Nicholas T. Longford, Mathematical Reviews, April, 2022)
“This book is readily usable for self-study, a graduate seminar, or use by a practitioner getting their bearings in the field. The book is filled with references to both foundational work and cutting-edge approaches. … the book was an easy read. Rosenbaum provides practical advice, delivered in a conversational tone, and steers clear of theweeds that might bog a reader down in the main text. steers clear of the weeds that might bog a reader down in the main text.” (Sara Stoudt, MAA Reviews, July 24, 2021)
Paul R. Rosenbaum is the Robert G. Putzel Professor of Statistics at the Wharton School of the University of Pennsylvania. He is a fellow of the American Statistical Association. In 2019, he received the R. A. Fisher Award, and in 2003 the George W. Snedecor Award, both from the Committee of Presidents of Statistical Societies (COPSS). He is the author of Observation and Experiment: An Introduction to Causal Inference (2017) and Observational Studies, 2nd edition (Springer 2002).
| SKU | Unavailable |
| ISBN 13 | 9783030464042 |
| ISBN 10 | 3030464040 |
| Title | Design of Observational Studies |
| Author | Paul R Rosenbaum |
| Series | Springer Series In Statistics |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2020-07-14 |
| Number of pages | 547 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |