A missingness mechanism is ignorable for likelihood or Bayesian inference about outcome-model parameters when the missingness-model factor can be omitted without changing that inference. Missing at random together with distinct outcome and missingness parameters is a standard sufficient condition.
Outcome and missingness parameters are distinct when their joint parameter space is the Cartesian product of their separate parameter spaces, so variation-independent choices can be made for the two models.
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