Missing Data

PROC MI Added to SASPy

I’m excited to announce that the new SAPy v4.6.0 release includes a pull request of mine that adds PROC MI to the SAS/STAT procedures directly exposed in SASPy. This procedure allows you to analyze missing data patterns and create imputations for missing data.

Missing Data Mechanisms

Understanding whether a variable’s missingness from a dataset is related to the underlying value of the data is a key concept in the field of missing data analysis. We distinguish three broad categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR).