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We built an adjusted model in multivariate regression to analyze the independent variables associated with in-hospital death: age, family history of CAD, prior coronary artery disease, hypertension, smoking, diabetes, categorical admission blood glucose < or ≥ 200 mg/dL, gender, ejection fraction and serum creatinine.
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By averaging the optimism an adjusted model will be generated.
Based on preliminary analyses, as well as consideration of known factors related to OA, we built our final adjusted model with the inclusion of BMI, age, gender, and disease severity (as measured by OA grade).
Logistic regressions were performed using all factors associated with activity in an initial unadjusted analysis and likelihood ratio tests were used to build the adjusted model.
Logistic regression was performed using all factors associated with obesity in an initial unadjusted analysis and likelihood ratio tests were used to build the adjusted model.
Logistic regression was used to build the adjusted model.
"We have built a solid model.
We built a confounder model without including air pollutants.
Two parallel multivariable models were built: an APACHE score and age-adjusted model; and a SOFA score and age-adjusted model.
We evaluated all kinds of factors, and selected three major ones of farm, genotype and breed to build a reduced adjusted linear model: 1 where Y ijk is trait measurement, μ is overall population mean, F i is farm, G j is genotype effect, B k is breed, and E ijk is random error.
"We actually built a model".
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