missing data mechanism

Multiple Imputation in a Nutshell

September 20th, 2021 by

Updated 9/20/2021

Imputation as an approach to missing data has been around for decades.

You probably learned about mean imputation in methods classes, only to be told to never do it for a variety of very good reasons. Mean imputation, in which each missing value is replaced, or imputed, with the mean of observed values of that variable, is not the only type of imputation, however. (more…)

When Listwise Deletion works for Missing Data

February 25th, 2014 by

You may have never heard of listwise deletion for missing data, but you’ve probably used it.

Listwise deletion means that any individual in a data set is deleted from an analysis if they’re missing data on any variable in the analysis.

It’s the default in most software packages.

Although the simplicity of it is a major advantage, it causes big problems in many missing data situations.

But not always.  If you happen to have one of the uncommon missing data situations in which (more…)

How to Diagnose the Missing Data Mechanism

May 20th, 2013 by

One important consideration in choosing a missing data approach is the missing data mechanism—different approaches have different assumptions about the mechanism.

Each of the three mechanisms describes one possible relationship between the propensity of data to be missing and values of the data, both missing and observed.

The Missing Data Mechanisms

Missing Completely at Random, MCAR, means there is no relationship between (more…)