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We used a separate logistic regression model for each variable that is, PEEP, tidal volume, and plateau pressure.
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We used a separate bivariate logistic regression model for newly diagnosed asthma.
Then a separate logistic regression was used to analyse if serum biomarkers could predict the PA/A ratio.
Using the admission diagnosis, hospitalizations were grouped into "Primary Conditions," and a separate logistic regression model was created for each group.
Each row is a separate logistic regression analysis.
Each row in the logistic regression tables below denotes a separate logistic regression model.
Each source of ETS exposure was evaluated in a separate logistic regression model.
A separate logistic regression model was calculated for every risk factor.
Always use a separate conditioner.
Because of interactions between socio-demographic variables and cancer (P < 0.001 for all), in subsequent analysis we used a series of separate logistic regression models for each cancer.
We used separate logistic mixed-effects models with a random school effect to estimate associations for each exposure and dichotomous outcome, and used linear mixed-effects models to estimate associations between each exposure and BMI z-scores.
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