- Thread starter
- #1

Hi folks.

Just looking for some input please.

I have a dataset containing interval data (one dependent and 6 independent variables) and taken a random 90% sample (approx 300 observations). I've performed a linear stepwise regression on the 90%, in order to obtain a model to predict the dependant using a number of input variables. I'm confident that I've done this ok.

The issue comes with testing the model. I'm sure that this is probably a simple step but, for some reason, I'm really struggling with it and would be grateful for some advice.

In order to test the model, I'm using the 10% of the dataset that were not used in the linear regression. I've input the predictor variables into the model, which has given me an expected value. I now want to compare this to the actual value. I was originally going to use Chi Square but that seems to be probability based and I'm not sure it's appropriate.

I've been told Spearman's rho would probably be most appropriate although I'm still not 100% sure that's right. Essentially, I would only be testing whether my predicted values = actual values.

All help appreciated. Thanks in advance.

Just looking for some input please.

I have a dataset containing interval data (one dependent and 6 independent variables) and taken a random 90% sample (approx 300 observations). I've performed a linear stepwise regression on the 90%, in order to obtain a model to predict the dependant using a number of input variables. I'm confident that I've done this ok.

The issue comes with testing the model. I'm sure that this is probably a simple step but, for some reason, I'm really struggling with it and would be grateful for some advice.

In order to test the model, I'm using the 10% of the dataset that were not used in the linear regression. I've input the predictor variables into the model, which has given me an expected value. I now want to compare this to the actual value. I was originally going to use Chi Square but that seems to be probability based and I'm not sure it's appropriate.

I've been told Spearman's rho would probably be most appropriate although I'm still not 100% sure that's right. Essentially, I would only be testing whether my predicted values = actual values.

All help appreciated. Thanks in advance.

Last edited: