Regression and Other Stories

Regression and Other Stories
ISBN-10
1108907350
ISBN-13
9781108907354
Category
Mathematics
Language
English
Published
2020-07-23
Publisher
Cambridge University Press
Authors
Jennifer Hill, Andrew Gelman, Aki Vehtari

Description

Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.

Other editions

Similar books

  • Regression and other stories
    By Jennifer Hill, Andrew Gelman, Aki Vehtari

    Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression.

  • Data Analysis Using Regression and Multilevel/Hierarchical Models
    By Jennifer Hill, Andrew Gelman

    The intervention for low - birth - weight children is described by Brooks - Gunn , Liaw , and Klebanov ( 1992 ) and Hill , Brooks - Gunn , and Waldfogel ( 2003 ) . Imbalance plots such as Figure 10.3 are commonly used ; see Hansen ...

  • Teaching Statistics: A Bag of Tricks
    By Andrew Gelman, Deborah Nolan

    Part I of the book presents a large selection of activities for introductory statistics courses and combines chapters such as, 'First week of class', with exercises to break the ice and get students talking; then 'Descriptive statistics' , ...

  • Bayesian Data Analysis, Third Edition
    By Donald B. Rubin, Andrew Gelman, John B. Carlin

    Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin. Murray, J. S., Dunson, D. B., Carin, L., and Lucas, J. E. (2013). ... Neal, R. M. (1993). Probabilistic inference using Markov chain Monte Carlo ...

  • Regression Analysis: A Constructive Critique
    By Richard A. Berk

    Rosenbaum , P. , and D.B. Rubin ( 1983a ) “ Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study With a Binary Outcome . ” Journal of the Royal Statistical Society , Series B 45 : 212-218 .

  • Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis
    By Frank E. Harrell

    This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".

  • Regression Analysis by Example
    By Ali S. Hadi, Samprit Chatterjee

    This new edition features the following enhancements: Chapter 12, Logistic Regression, is expanded to reflect the increased use of the logit models in statistical analysis A new chapter entitled Further Topics discusses advanced areas of ...

  • A Student’s Guide to Bayesian Statistics
    By Ben Lambert

    Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics.

  • Statistics for Health Data Science: An Organic Approach
    By Ruth Etzioni, Micha Mandel, Roman Gulati

    For contingency tables, this is known as Pearson's residual: Observed√ Predicted . Res = Predicted − Pearson's residual tells us about overprediction and underprediction within each cell of the table. To summarize across groups, ...

  • Causal Inference
    By Scott Cunningham

    Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It's rare that a book prompts readers to expand their outlook; this one did for me.