Noisy Data: Incorporating Variability into Your Analysis
Richard Schwartz
10.1044/cred-ai-bts-001
Noisy data has a high degree of variability and a greater range -- of scores, or reaction times, or whatever it is you're measuring. In a lot of the cochlear implant studies we're doing now, we're using eye tracking. So for us it would be more variability in how they ... Continue to Article >>
Event-Based Measures of Effect Size
Chris Dollaghan
10.1044/cred-ai-ps-cpri001
The following slides accompanied a presentation delivered at ASHA's Clinical Practice Research Institute. Event-based measures of treatment effects Another approach to analyzing data from group comparison studies. Instead of comparing means, dichotomize the event (outcome) of interest as “present” or “absent” in individual patients within the groups. Then compare the ... Continue to Article >>