Is it necessary to scale a signal for quantization noise analysis?
No, you don't need to scale the stimulus up to the full bit depth. That would actually end up underestimating the effect that roundoff noise would have on your actual system, as you would be artificially increasing the signal power (thus lowering the predicted signal to quantization noise ratio). 

It makes sense to simulate the filter with a range of inputs that covers the space that you're designing the system to operate with. If the inputs will always be in the range $[-1, 1]$, then simulate using that range. On the other hand, if it's very likely that the data will be in that range, but possible that it might be larger, then it would be appropriate to test at higher levels. This requirement would likely be driven by higher-level considerations in your design.