Applied missing data analysis in the health sciences /

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A modern and practical guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatistics With an emphasis on hands-on applications, Applied Missing Data Analysis in the Health Sciences outlines the various modern statistical methods for the analysis...

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Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: Zhou, Xiao-Hua (Auteur), Zhou, Chuan, 1972- (Auteur), Liu, Danping, 1981- (Auteur), Ding, Xiaobo (Auteur)
Format: Électronique eBook
Langue:Inglés
Publié: Hoboken, New Jersey : John Wiley & Sons, [2014]
Collection:Statistics in practice.
Sujets:
Medical statistics.
Medicine > Research > Statistical methods.
Data Interpretation, Statistical
Biomedical Research > methods
Models, Statistical
Research Design
Médecine > Recherche > Méthodes statistiques.
HEALTH & FITNESS > Holism.
HEALTH & FITNESS > Reference.
MEDICAL > Alternative Medicine.
MEDICAL > Atlases.
MEDICAL > Essays.
MEDICAL > Family & General Practice.
MEDICAL > Holistic Medicine.
MEDICAL > Osteopathy.
Accès en ligne:Texto completo (Requiere registro previo con correo institucional)
Table des matières:
  • Missing data concepts and motivating examples
  • Overview of methods for dealing with missing data
  • Design considerations in the presence of missing data
  • Crosssectional data methods
  • Longitudinal data methods
  • Survival analysis under ignorable missingness
  • Nonignorable missingness.

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