![]() ![]() In this case the missing data are considered to have occurred at random conditional on one or more observed variables. While Listwise deletion requires the data to be MCAR in order to obtain valid inferences, Multiple imputation will also lead to valid results if the missing data are missing at random (MAR Little & Rubin, 2002, p. Secondly, Multiple imputation makes less stringent assumptions about the missingness mechanism. Firstly, unlike Listwise deletion, Multiple imputation uses all available data and does not throw away any information. Multiple imputation has several advantages over Listwise deletion. ![]()
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