Dropping Missing Observations under MAR Assumption


Some of the outcome data in my data set are missing. I believe that the missing data mechanism is missing at random (MAR) as the observed characteristics significantly differ between the missing and non-missing data but there is no theoretical background supporting that there are unobserved factors that can determine if the data is missing or not.

I want to drop the missing observations instead of using an imputation method. However, I am not sure how to prevent bias. I can control for the factors that explain if the data is missing or not simply by adding them into regression but I am not sure if this would be enough.


Posted 2020-10-23T21:31:13.807

Reputation: 1

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