This question is similar to Missing input value during prediction of a generalized linear model.
Consider the following scenario:
I fitted a linear regression model on a training dataset with sometime-missing predictor variables. Some imputation strategy was employed to ensure that a missing indicator variable is not involved.
Now I would like to use the fitted model to perform prediction on a new dataset, which also has issue with sometime-missing predictor variables. Here are my questions:
How should I go about applying the model? My first reaction is that - however imputation strategy is employed in the model fitting, perform it on the new dataset and then apply the fitted model. If I go down that path, do I need to make adjustment for the fact that imputed data is used?
What if I have no information on what imputation strategy had been employed when the model was developed? (e.g. the model was developed by another researcher)