Testing the difference between two independent regression coefficients I would like to test the difference between two independent regression coefficients. David C. Howell's book 'Statistical Methods for Psychology' (Chapter 9.11) suggests that there is a t-test for differences between two independent regression coefficients.
How would this be done in R?
I currently have these 2 regressions looking at peoples Importance to Donate based on their Guilt, Percieved Responsibility and Negative Feelings: 
aov_Individual <- aov(AV_importance_to_donate~AV_guilty+AV_percieved_resp+feeling_I)


aov_Statistical <- aov(AV_importance_to_donate~AV_guilty+newdata_S$AV_percieved_resp+feeling_S)

I believe I can extract the coefficients with the following code:
aov_Independent$coefficients[2]
aov_Statistical$coefficients[2] 

But I do not know how to preform the t-test to compare the coefficients from there...
 A: rbind your two data sets (i.e. put them under each other), add your two types as new column, run aov with interactions. The interactions compare coefficients in the same model (as suggested by Roland and whuber in the comments):
mydata <- rbind(individualData, statisticalData)
# make new column for factor "individual" or "statistical":
mydata$indstat <- rep(c("ind", "stat"), each=c(nrow(individualData), nrow(statisticalData))
summary(aov(AV_importance_to_donate ~ (AV_guilty+AV_percieved_resp+feeling_I + feeling_S)*indstat, data=mydata))

You will now get the main effects for each of your predictors in the brackets, the main effect of "indstat" as well as the interactions of each of them with "indstat".
When the interaction is significant, your two data sets differ with respect to that coefficient.
(Note that you use newdata_S$AV_percieved_resp which seems to be a different variable. Obviously you can interpret interactions only if the predictors mean the same thing. Also note that you now have feeling_S and feeling_I in the model, although it is only one of the each in the original.)
(I have difficulties finding such examples on CV to point to, although there must by now be hundreds of them.)
