I have a data set that comes close to fitting neatly in a tabulate output. All of the X's are categorical. All of the Y's are continuous. There are some combinations of x's, however that have very few data points or no data points, so I get an unreliable or non-existent Y.
To solve this problem, I want to use Fit Model. I can get a very reasonably looking model
One point for example:
Perhaps one option for you could be "Output grid table" under the red triangle of the prediction profiler.
alternatively, one of the LSmeans options can be useful. you will find them under the red triangle of the leverage plots.
I'm not sure if the values in your first 'Tabulate' are predicted or actual values. In any case, though, if you want to estimate or impute missing cells in this tabulation, you could:
You could use JSL to automate this if you wanted to.
But I'm not sure I have understood your question correctly.
Always nice to have options on how to solve the problem.
There shouldn't be any difference between saving the predicted value to a column and saving the prediction formula to a column, right? The formula might just be helpful if I were using that prediction with another data set?
Yes, that's correct - If you add a new row to the table that has the required 'x values', then the 'y value' computed by the formula will just appear in the appropriate cell automatically.