5. In Example 14.3, use an MNAR model to generate missing values in y2, namely Ri ...

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5. In Example 14.3, use an MNAR model to generate missing values in y2, namely Ri ∼ Bern(πi ), Probit(πi ) = η0 + η1Yi2, where η0 = 0, η1 = 1. At the imputation stage generate five complete datasets in two ways, first with the MAR MI approach used in Example 14.3, and second using an MNAR MI model

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How does using the alternative imputation datasets affect results from the final pooled inference stage?

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