Name: Statistical Analysis With Missing Data (Wiley Series in Probability and Statistics) (en Inglés)
Price: 126950.00 CLP
Availability: InStock
Author: Roderick J. A. Little; Donald B. Rubin
ISBN: 9780470526798

portada Statistical Analysis With Missing Data (Wiley Series in Probability and Statistics) (en Inglés)

Formato

Libro Físico

Editorial

Wiley

Autor

Roderick J. A. Little; Donald B. Rubin

Año

2019

Idioma

Inglés

N° páginas

449

Encuadernación

Tapa Dura

ISBN13

9780470526798

N° edición

Categorías

Probabilidad y estadística

Statistical Analysis With Missing Data (Wiley Series in Probability and Statistics) (en Inglés)

Roderick J. A. Little; Donald B. Rubin (Autor) · Wiley · Tapa Dura

Libro Físico

$ 126.950

$ 211.590

Ahorras: $ 84.640

40% descuento

Envío normal

Origen: Reino Unido (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Miércoles 15 de Mayo y el Martes 21 de Mayo.

Lo recibirás en cualquier lugar de Chile entre 1 y 3 días hábiles luego del envío.

Reseña del libro "Statistical Analysis With Missing Data (Wiley Series in Probability and Statistics) (en Inglés)"

AN UP-TO-DATE, COMPREHENSIVE TREATMENT OF A CLASSIC TEXT ON MISSING DATA IN STATISTICS The topic of missing data has gained considerable attention in recent decades. This new edition by two acknowledged experts on the subject offers an up-to-date account of practical methodology for handling missing data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism, and then they apply the theory to a wide range of important missing data problems. Statistical Analysis with Missing Data, Third Edition starts by introducing readers to the subject and approaches toward solving it. It looks at the patterns and mechanisms that create the missing data, as well as a taxonomy of missing data. It then goes on to examine missing data in experiments, before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include recent work on topics such as nonresponse in sample surveys, causal inference, diagnostic methods, and sensitivity analysis, among a host of other topics. An updated "classic" written by renowned authorities on the subject Features over 150 exercises (including many new ones) Covers recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods Revises previous topics based on past student feedback and class experience Contains an updated and expanded bibliography Statistical Analysis with Missing Data, Third Edition is an ideal textbook for upper undergraduate and/or beginning graduate level students of the subject. It is also an excellent source of information for applied statisticians and practitioners in government and industry.