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- W55705431 abstract "Publisher Summary This chapter explores those statistical issues that arise from missing data and uses current population surveys to illustrate these ideas. Many basic problems are introduced via simple examples. The chapter presents the taxonomy of these methods. The explicit modeling approach is a flexible but principled way to proceed in practice. The chapter discusses the computational methods for the analysis of incomplete data. It also outlines various methods for handling incomplete data and describes the modeling approach to incomplete data. A principled approach to the problem of missing data in large databases requires a plausible model for the missing data mechanism and estimation procedures that remove or minimize biases introduced by the incompleteness of the data." @default.
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- W55705431 date "1983-01-01" @default.
- W55705431 modified "2023-09-25" @default.
- W55705431 title "MISSING DATA IN LARGE DATA SETS" @default.
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- W55705431 doi "https://doi.org/10.1016/b978-0-12-765480-5.50017-5" @default.
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