Question

. ________ is the process of finding the most appropriate estimate for missing data.
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Answer 1

Multiple Imputation (MI) is a statistical technique for handling missing data. The key concept of MI is to use the distribution of the observed data to estimate a set of plausible values for the missing data.

Answer 2

Answer:

Multiple Imputation (MI) is the process of finding the most appropriate estimate for missing data.

Step-by-step explanation:

• Multiple Imputation (MI) is a statistical technique for handling missing data.
• The key concept of MI is to use the distribution of the observed data to estimate a set of plausible values for the missing data.
• Multiple imputation is essentially an iterative form of stochastic imputation.
• Here instead of filling in a single value, the distribution of the observed data is used to estimate multiple values that reflect the uncertainty around the true value.