I'm fitting a RD(Huggins) model with one covariate. When I ask for real parameter predictions with the default (mean) covariate values, I get answer "A" for the BetaHats (and NHats). When I ask for predictions when setting the covariate to a different value, I get answer "B". When I set the covariate value for another covariate not in the model I get answer "C".
The BetaHats and NHats should not change when I change the covariate value for real parameter prediction. And they should especially not change when I'm changing the value for a covariate that's not even in the model.
I have the example in a DBF file for examination. I'm copying some output below so you can see I'm not crazy (look at the BICs). I can post the BetaHats, too, if you need further convincing.
So, what's going on here? Thanks!
Geof
Note: in the results below, the mean covariate value for the covariate in the model ("iscore") is .8929224. The covariate "numz" is in none of these models. The modest changes in BIC belie much larger changes in BetaHats and NHats.
- Code: Select all
---------------------------------------------------------------------------------------------------------------------
Delta BIC Model
Model BIC BIC Weight Likelihood #Par Deviance
---------------------------------------------------------------------------------------------------------------------
{iscore; default covariate values} 2147.787 0.00 0.34432 1.0000 8.0000 2091.127
{iscore; set cov for reals = iscore=.8929224} 2147.961 0.17 0.31573 0.9170 8.0000 2091.300
{iscore; set cov for reals = iscore=.8929224 and numz=4} 2148.357 0.57 0.25894 0.7520 8.0000 2091.697
{iscore; set cov for reals = iscore=2} 2150.708 2.92 0.07992 0.2321 8.0000 2094.048
{Null model (no covariates)} 2159.306 11.52 0.00109 0.0032 7.0000 2109.728
---------------------------------------------------------------------------------------------------------------------