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Exact(38)
All specifications control for age, a quadratic term for age, education indicators, gender, and race.
The control variables include gender, immigrant status, a linear variable for education and age, a quadratic term for age and whether individual i lives in a single household, has child custody, has more than one employer, is currently studying, is a director, holds a permanent position or works shift work.
We categorized BMI and introduced a square term for age to meet linearity with the outcomes.
For most variables, the linear term for age produced the best fit.
A quadratic term for age was of a small magnitude and not statistically significant (p = 0.52).
To allow for a possible non-linear relationship, a quadratic term for age was added.
Similar(22)
Adjusted odds ratios were estimated by multivariable logistic regression models with inclusion of covariate terms for age, race, gender, Deyo-Charlson Index, patient type (medical versus surgical), sepsis and number of organs with acute failure.
Briefly, predicted FEV1 values were modelled in our dataset for each gender in non-smoking, non-asthmatic, non-wheezing individuals with terms for age, height, age-squared and age-height interactions.
Models included fractional polynomial terms for age and BMI.
*Also included fractional polynomial terms for age, which were age−0.5, age−0.5 ln age).
The model included also terms for age (one-year age group) and tumour grade.
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CEO of Professional Science Editing for Scientists @ prosciediting.com