Handling Missing Values in Matrices of Observations

Summary Statistics provides the Multiple Imputation (MI) method VSL_SS_METHOD_MI to deal with missing values in a dataset. A typical usage flow is as follows:

  1. In the MI paradigm, replace each missing value with a set of m values predicted from the underlying distribution.

  2. After MI application, analyze each of the m complete datasets producing estimates and standard errors.

  3. Combine the results of the first two steps according to the rules in [Rubin1987] to produce overall estimates and standard errors.

MI approach is integrated into the library as described in [Schafer1997].

See Also

Basic Assumptions under the MI Method
Basic Components of the MI Method

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