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. U...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Gelman, Andrew 1965- (VerfasserIn), Hill, Jennifer 1969- (VerfasserIn), Vehtari, Aki (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Cambridge Cambridge University Press 2021
Schriftenreihe:	Analytical methods for social research
Schlagworte:	Regressionsanalyse
Zusammenfassung:	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
Beschreibung:	XV, 534 Seiten Diagramme
ISBN:	9781107676510 9781107023987