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Can I use "custom test" to calculate errors for parameter combinations in a linear model

I have a linear model of the form yval = grp + xval + grp*xval, where grp is categorical with two levels and xval is continuous.   That I am running in JMP v. 8, with that Fit Model dialog. 

JMP parameterizes it as

intercept + grp(level1) + xval + xval*grp(level1)

I want to know the estimate and standard errors for an overall intercept and slope for each of my two levels of grp.  I can do this if I rerun the model separately for each level of group, but is there a way to do it with the model output from the full model?  I tried using custom tests and I can get roughly the same parameter estimates as when I do two separate regressionsjmp_* , but the standard errors are very different.  Which is the more valid standard error to use?

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