Mispronunciation detection tools could increase treatment access for speech sound disorders impacting, e.g., /ɹ/. We show age-and-sex normalized formant estimation outperforms cepstral representation for detection of fully rhotic vs. derhotic /ɹ/ in the PERCEPT-R Corpus. Gated recurrent neural networks trained on this feature set achieve a mean test participant-specific F1-score =.81 (σx=.10, med = .83, n = 48), with post hoc modeling showing no significant effect of child age or sex.