Does using individual probabilities and confidence intervals improve the accuracy of classifying non-responders to exercise training compared to threshold-based dichotomous classification?
Using individual probabilities and confidence intervals rather than simple dichotomous thresholds improves the accuracy of identifying true non-responders to exercise training.
We examined maximal oxygen consumption responses following exercise training to demonstrate the limitations associated with threshold-based dichotomous classification of responders and non-responders and proposed alternative methods for classification. Specifically, we: 1) calculated individual probabilities of response, and 2) classified individuals using response confidence intervals (CI) and reference points of zero and a smallest worthwhile change of 0.5 METs. Our findings support the use of individual probabilities and individual CIs to improve the accuracy in non-response classification.
Bonafiglia et al. (Thu,) studied this question.
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