How to test forecasting accuracy of regression model?

[dune2]

Hey, I have just finished running all the regressions for my thesis and I now have a nice 8-variable regression with an r² if 0.53. Almost all my hypothezised variables are significant. I am now wodering if there is a possibility to somehow test the forecasting accuracy of this model? I am using SPSS, is there anything that comes to mind? I just want to say something like: here is the printout, all is significant. Here is the forecasting equation, coefficients 1 though 8 do blablabla, forcasting accuracy is X. Is that possible?

 

[0rthodontist]

Well you sound like you know more than I do but I know that when you are working with neural networks, you train the network on only part of the data, and you reserve the rest of the data to test the accuracy of the network--to see if the network correctly "predicts the past." Maybe you can see if your model correctly "predicts the past" if you have data available for testing that has not been input into your model.

 

[EnumaElish]

You should first state the value of the "F" statistic for the overall regression.

It is possible to construct a confidence interval for the forecast; you first need to compute the standard error of the forecast. Then (lower bound, upper bound) = (Yhat - SE_Yhatt_c, Yhat + SE_Yhatt_c) where Yhat is the point forecast, SE is the standard error of Yhat, and t_c is the critical t (= approx. 2).

See http://www.rand.org/pubs/papers/P4365/

 

[dune2]

Ah, thanks!