Model Selection with Missing Data Embedded in Missing-at-Random Data
When models are built with missing data, an information criterion is needed to select the best model among the various candidates. Using a conventional information criterion for missing data may lead to the selection of the wrong model when data are not missing at random. Conventional information cr...
Main Authors: | Keiji Takai, Kenichi Hayashi |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-04-01
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Series: | Stats |
Subjects: | |
Online Access: | https://www.mdpi.com/2571-905X/6/2/31 |
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