Applied Missing Data Analysis Enders Craig K.
Applied Missing Data Analysis Enders Craig K. The most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling…
Specifikacia Applied Missing Data Analysis Enders Craig K.
Applied Missing Data Analysis Enders Craig K.
The most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling missing data more effective. State-of-the-art technical literature on missing data is translated into accessible guidelines for applied researchers and graduate students. The second edition includes new methods based on factored regressions, newer model-based imputation strategies, and innovations in Bayesian analysis.
Consistently organized chapters explain the rationale and procedural details for each technique and illustrate the analyses with engaging worked-through examples on such topics as young adult smoking, employee turnover, and chronic pain. The The second edition takes an even, three-pronged approach to maximum likelihood estimation (MLE), Bayesian estimation as an alternative to MLE, and multiple imputation.
Applied Longitudinal Data Analysis
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Applied Thematic Analysis
Data Analysis
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