Prediction interval - Linear regrission

[aosmith]

I have some guesses, but it's hard to troubleshoot without your model and an example dataset. Could you include a dataset and your model code so your question is reproducible?

If you've never made a reproducible example (i.e., "reprex") before, you can see an explanation and some suggested reading material here:

FAQ: What's a reproducible example (`reprex`) and how do I create one?

Why reprex? Getting unstuck is hard. Your first step here is usually to create a reprex, or reproducible example. The goal of a reprex is to package your code, and information about your problem so that others can run it and feel your pain. Then, hopefully, folks can more easily provide a solution. What's in a Reproducible Example? Parts of a reproducible example: background information - Describe what you are trying to do. What have you already done? complete set up - include any library() calls and data to reproduce your issue. data for a reprex: Here's a discussion on setting up data for a reprex make it run - include the minimal code required to reproduce your error on the data…

Note that one reason for getting predictions for the original dataset instead of the new dataset for lm objects is if you don't have a variable in the new dataset with the same name as the explanatory variable in your model.