In this paper, we attempt to provide a simple taxonomy for incomplete-data problems and at the same time develop unified methods of analysis. The emphasis is on techniques which are natural extensions of the complete-data analysis and which will handle rather general classes of incomplete-data problems as opposed to custom-made techniques for special problems. The principle of estimation is either maximum likelihood or is at least based on maximum likelihood.
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Hartley et al. (1971) studied this question.