Multivariate normal samples may contain both complete and incomplete data vectors. In this paper, expressions are developed showing the gain in precision which may be obtained by using the incomplete as well as the complete data when estimating parameters. The problem of designing data collection procedures to yield incomplete data so as to minimize the cost of collecting the data while achieving desired precision of estimates is discussed. A common special case of this problem is shown to have a simple solution.
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Hocking et al. (1972) studied this question.
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