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For the main results variable (DWM1), linear regression models will be constructed, adjusted for the baseline level and analysing per ITT.
To adjust for possible confounders and to detect potential interactions with the "treatment group" variable, logistic regression models will be constructed, adjusted for the baseline level.
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Multivariate Andersen-Gill proportional hazards models were constructed, adjusting for sexual behavioral and demographic variables.
To determine the independent association, a logistic model was constructed adjusting for age and sex.
Two groups of unconditional logistic regression models both for overweight and hypertension (SBP≥140 mmHg or DBP≥90 mmHg) were constructed adjusting for well-known determinants.
To determine the independent association between health care use and being homeless, a logistic regression model was constructed adjusting for age and sex.
Multivariable linear regression models were constructed adjusting for potential confounders including current BMI, age, race, and age of first live birth, and interaction terms were generated for the genotype of each SNP compared to a baseline genotype.
To assess the migration of organizations from a model of organization to another between 2005 and 2010, two-level regression models with organizations nested within territories will be constructed, adjusting for 2005 results.
Case-control and case-crossover designs were used to assess the risk of hospitalisation with conditional logistic regression models constructed and adjusted for 270 conventionally hepatotoxic drugs.
Alpha path, the effect of the intervention on the theoretical construct, is adjusted for baseline consistent condom use and the theoretical construct.
Multivariate regression models were constructed to adjust for baseline differences between SSRI and control groups.
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