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. Author manuscript; available in PMC: 2022 Oct 20.
Published in final edited form as: Cerebellum. 2018 Aug;17(4):404–418. doi: 10.1007/s12311-018-0923-8

Table 4.

Logistic regression models predicting CMI status from response time and pain-related factors

a Single-task emotion perception B Wald Z p OR 95% CI
SFMPQ pain 0.070 3.75 < 0.001 1.077 [1.168 2.139]
DASS depression − 0.312 − 2.59 0.010 0.732 [0.004 0.723]
DASS anxiety 0.435 2.85 0.004 1.545 [0.565 0.910]
Response time 0.001 0.67 0.503 1.001 [0.998 1.005]
b Dual-task emotion perception B Wald Z p OR 95% CI
SFMPQ Pain 0.069 6.14 < 0.001 1.072 [1.050 1.097]
DASS Depression − 0.293 − 4.29 < 0.001 0.746 [0.647 0.847]
DASS Anxiety 0.428 5.14 < 0.001 1.533 [1.312 1.819]
Response Time 0.001 2.35 0.019 1.001 [1.000* 1.002]

B parameters reflect the log odds of being a CMI patient for a one unit increase in the predictor variable. For future comparison, the Akaike Information Criterion (AIC) for the two models were as followed – single task = 103.45; dual-task = 286.11

DASS 21-item Depression, Anxiety, and Stress Scale, SFMPQ short-form McGill Pain Questionnaire

*

Lower bound = 1.0002