I'm finishing up a presentation that I'll be giving at AAPOR (Saturday, May 15th at 2:15) on using imputation methods to estimate "e." I posted on this topic a while ago. I wanted to post one of the graphics that I developed for that presentation.
I start from a very simple model that predicts eligibility using the natural logarithm of the last call number as the only predictor. That generates the following distribution of imputed eligible cases.
The blue line shows the eligibility rates for the cases for which the eligibility status is known. The blue dashed line shows the model (a logistic regression model predicting eligibility using the natural log of the call number) prediction of eligibility. The green line shows the eligibility for the cases where the eligibility flag is imputed. The green line is the line used to estimate "e."
I start from a very simple model that predicts eligibility using the natural logarithm of the last call number as the only predictor. That generates the following distribution of imputed eligible cases.
The blue line shows the eligibility rates for the cases for which the eligibility status is known. The blue dashed line shows the model (a logistic regression model predicting eligibility using the natural log of the call number) prediction of eligibility. The green line shows the eligibility for the cases where the eligibility flag is imputed. The green line is the line used to estimate "e."
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