Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research.
Applied missing data analysis. New York: The Gilford Press, 2010.Enders C.K. (2010). Applied missing data analysis. The Guilford Press, New York.Enders, C. K. (2010). Applied missing data analysis. New York, NY: The Guilford Press....
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Chapter 8: Multilevel Missing Data Chapter 9: Missing Not at Random Processes Chapter 10: Special Topics and Applications Chapter 11: Wrap-Up Reviews "The second edition of Applied Missing Data Analysis is a bold, top-to-bottom revision that makes a phenomenal book even better. This book is...
Applied Missing Data Analysis 来自 ResearchGate 喜欢 0 阅读量: 556 作者: CK Enders 摘要: Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. ...
1.3 Missing Data Patterns. 1.4 A Conceptual Overview of Missing Data heory. 1.5 A More Formal Description of Missing Data Theory. 1.6 Why Is the Missing Data Mechanism Important? 1.7 How Plausible Is the Missing at Random Mechanism? 1.8 An Inclusive Analysis Strategy. 1.9 Testing the Missing ...
《Applied Missing Data Analysis in the Health Sciences》(Xiao-Hua Zhou)内容简介:With an emphasis on hands-on applications, Applied Missing Data Analysis in the Health Sciences outl...
Applied Longitudinal Data Analysis 1&2 热度: Applied Longitudinal Data Analysis - Modeling Change and Event Occurrence 热度: . ST732 AppliedLongitudinalDataAnalysis LectureNotes M.Davidian DepartmentofStatistics NorthCarolinaStateUniversity c2005byMarieDavidian ...
Due to cluster instability, not in the cluster monitoring system. This paper focuses on the missing data imputation processing for the cluster monitoring a
MICE - it assumes that the missing data are Missing at Random (MAR), which means that the probability that a value is missing depends only on observed value and can be predicted using them. Amelia - It assumpes that All variables in a data set have Multivariate Normal Distribution (MVN)....