For example, if we have a large data set of MCT values of children. How can we categorize the values into normal, subnormal and abnormal? Can we make a group having mean+- 1SD and so on? One other option could be comparing with published literature done in the of same age group of children but especially for MCT values it is almost impossible as every researchers have used their own stimulus protocol to determine the threshold values. Any ideas on this subject matter would be very helpful. Thank you.
Would agree is not a good idea to compare with published literature unless stimuli are exactly the same. But if you have a healthy (control) group, then as you say you can easily define the "normal" range in terms of the mean and SD of your controls - that is, use a "z-score" approach. Assuming a Gaussian distribution, being 1 SD below the mean puts you in the bottom 15%, 2 SDs in the bottom 2%, etc (http://en.wikipedia.org/wiki/Standard_score). Here for example is a paper using z-scores to compare impairments on two different kinds of motion stimuli (global motion and biological motion) - http://psych.mcmaster.ca/maurerlab/Publications/Hadad_Patients_2012.pdf -
the interest here is in having a measure comparable across stimuli rather than categorising individuals as "normal" or not - but you could easily do that too, you would just to pick some sensible criteria
Dear Marko,
Thank you so much. In our case, we have a cohort of children but unaware about their birth history (preterm, brain injury during birth etc.). However, we know their visual status according to their VA and stereo data. We are not too sure if visually normal children can be considered as controls or not. The purpose here being to observe the change in the MCT performance with age and relationship with other visual function, and cognition. But, the values at two different ages were obtained with 2 different stimuli. Even to explore the predictive utility of MCT at young age for their cognitive and motor development at school age we will need to know the cut off value for within normal or abnormal, so that we can analyze them as done in your paper ( Hyperopia and Movement ABC). Any more expert input would be very helpful. Thank you very much.
Regards,
Nabin
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