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We constructed these linear models by determining the effect of each binary variable relative to the mean ΔGdissociation.
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The variable GENDER is a binary variable equal to one for "female" admissions.
The predictor variable was a binary variable corresponding to randomization into the treatment or control arm.
The second model considered a binary variable corresponding to <3 versus 3 + days of formal practice.
For statistical purposes, we considered severe PSS as a binary variable (absent/present) according to a binary images/binary behaviour design [ 8].
For the purposes of calculating the OIS we will assume, for binary variables, a relative risk reduction or increase of 25%, an α of 0.05, a β of 0.20 and a median baseline risk from the available studies.
All models were adjusted for public holidays (as a binary variable), temperature and relative humidity (same lag as PM10, PMion, PMrest, the three individual ions, PM2.5, soot, geographical origin of air mass and limited/effective local dispersion).
Given that duration was a binary variable, this is unlikely to have resulted in substantial misclassification.
A binary variable was used in order to maximize the power available to assess interactions.
This binary variable also omitted persons considered to be 'underweight'underweight
For binary variables proportions and relative risks together with their associated 95% confidence-intervals are calculated.
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