I was wondering what is the English name for the index I_2, used to evaluate the goodness of the fit:

I_2= SQRT[ SUM(Y_i-y_i)^2/N]/SUM(Y_i)/N,

where

Y_i is the ith value of the variable to be predicted and y_i=m*X_i+q is the predicted value of Y_i. N is the number of points (Y_i, X_i).

Many Thanks,

hannibal ]]>

There are 8 continuous predictor variable and

My dependent variable is:

not used

slightly used

highly used

Is it ordinal or nominal?

Can I use multi-nominal regression in my case?

I am confused when i code my dependent variable them as 1,2 and 3 (kind of low,medium and high which gives me a feeling as if the order matters but when I say not used, slightly used and highly used it seems order does not matter.

Can anybody help?

thank you ]]>

10 independent continuous variable and 190 cases.

When I run ordinal regression(PLUM) every things seems fine expect I get this warning at the top.

There are 315 (63.5%) cells (i.e., dependent variable levels by observed combinations of predictor variable values) with zero frequencies.

I tried online but could not find any concrete answer.

Code:

`Model Fitting Information `

Model -2 Log Likelihood Chi-Square df Sig.

Final 248.139 82.702 10 .000

Link function: Logit.

Code:

` Chi-Square df Sig.`

Pearson 432.116 334 .010

Deviance 248.139 334 1.000

Link function: Logit.

I am trying to test hypothesis on effect of some of the predictor on dependent variable.

If I use multiple regression every thing looks fine but i don't think i can do that. ]]>