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A missing data mechanism is said to be ignorable for likelihood inference if the joint likelihood for the responses of interest and missing data indicators can be decomposed into two separate components (containing the parameters of main interest and the parameters of the missingness mechanism, respectively) and the parameters for each component are distinct in the sense that there are no parameter restrictions across the components.


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