Specifically, the multivariable model controlled for gender, size of residential area, educational level, and sleep quality (PSQI score >5).
The regression model controlled for age, sex, race, ethnicity, hospital ownership category, region, MSA status, payer, urgency at triage, alcohol, "high risk" associated diagnosis and hospital admission.
The model controlled for farm and cohort by a nested design and included a repeated measure on calf at each sampling occasion.
The regression model controlled for age, sex, race, hospital ownership, ethnicity, hospital status, region, MSA status, payer, urgency at triage, alcohol, "high risk" associated diagnosis and whether neuroimaging was performed.
The multivariate linear regression model controlled for confounders (gender, ASA, body mass index, race, smoking status, anesthesia type and comorbidities) previously found to be associated with the outcome (i.e. prolonged LOS).
The regression model controlled for sample member baseline characteristics and was weighted to account for differences by sites in each of the following aspects: site sample size (so each of the ten sites contributes equally to the results), survey response rates, and program versus control ratios.
Including age as a main effect in the DTI model controlled for age-related changes in white matter independent of ARQ, while using AdjARQ as the covariate of interest removed age as a confound on the behavioral parameter.
*Adjusted model controlled for age and BMI.
The model controlled for gender and age.
The multinomial model controlled for possible within-household influences.
This regression model controlled for the type of CAM practitioner.
