My thesis coach wants me to perform a predictive analysis based on OLS. What I understand is the following:
- divide the dataset into a training set and a holdout set, for instance 50-50
- perform OLS on the training set
- construct linear equation based on regression output
- create a new variable (DV2) in the holdout set, and use the linear equation to
calculate its values - now you have F (forecasted) and A (actual) DV values in the holdout set
- calculate the performance of the predictive linear equation with RMSE:
- a lower RMSE is better
Now, some questions about this procedure:
- Am I doing this right?
- I have no clue how to have SPSS perform the RSME operation, so can't I just do it in Excel? If I paste the holdout set into Excel, performing this calculation seems easy enough. Is there something I'm missing?
- If you know how to perform this calculation in SPSS, please let me know because I expect that SPSS might be able to output some extra insightful statistics and / or graphs
Best Answer
Compute your random sample definition, e.g.,
Run the regression. Include this subcommand
and this
You can do this by specifying a selection variable in the Regression dialog box and by using the Save subdialog.
Now select the other part of the data, e.g.,
Run Descriptives on
RES_1
.