Strategies to Fit Pattern-Mixture Models
Whereas most models for incomplete longitudinal data are formulated within the selection model framework, pattern-mixture models have gained considerable interest in recent years. In this chapter, we outline several strategies to fit pattern-mixture models, including the so-called identifying-restrictions strategy. Multiple imputation is used to apply this strategy to realistic settings, such as quality-of-life data from a longitudinal study on metastatic breast cancer patients.
KeywordsMultiple Imputation Conditional Density Advanced Breast Cancer Patient Miss Data Mechanism Dropout Process
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