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- Payer en toute sécurité
- Toujours un magasin près de chez vous
118,95 €
+ 237 points
Format
Description
Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and computational methods for analyzing incomplete data.
Suitable for graduate students and researchers in statistics, the book presents thorough treatments of:
- Statistical theories of likelihood-based inference with missing data
- Computational techniques and theories on imputation
- Methods involving propensity score weighting, nonignorable missing data, longitudinal missing data, survey sampling, and statistical matching
Assuming prior experience with statistical theory and linear models, the text uses the frequentist framework with less emphasis on Bayesian methods and nonparametric methods. It includes many examples to help readers understand the methodologies. Some of the research ideas introduced can be developed further for specific applications.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 223
- Langue:
- Anglais
Caractéristiques
- EAN:
- 9781439849637
- Date de parution :
- 23-07-13
- Format:
- Livre relié
- Format numérique:
- Genaaid
- Dimensions :
- 160 mm x 239 mm
- Poids :
- 458 g
