Sentence examples for models including gender from inspiring English sources

Relative hazards (RH) of dying were controlled in models including gender, education, medical and mental health, social relations, help given and received, and health behaviour.

Multiple regression models including: gender, aBMD and BTMs revealed TBS as an independent, discriminative variable with adjusted multiple R2 values of 69.1% for SMI, 79.5% for Tb.N, 68.4% for Tb.Sp, and 83.3% for BV/TV.

Logistic regression analyses of models including gender, body weight, baseline CD4 cell count, receiving anti-tuberculous drugs, and receiving fluconazole, were not significant predictors of elevated AST > 3 times from baseline (χ2 (5, N = 328) = 3.72, p = 0.592) and elevated ALT > 3 times from baseline (χ2 (5, N = 188) = 7.26, p = 0.298).

All models included gender, years of education, and age at entry as covariates.

As for confounding factors, the statistical models included gender, age, and year of measurement.

The models included gender, FEV1, FVC, TLC, final Borg score, lowest SpO2 (distance model only), PaO2, presence of CT fibrosis, treatment status and presence of PH.

Covariates in the models included gender, plan type, pre- and post-index concomitant medications, history of diabetes-related comorbidities, and patient copayment, among other explanatory variables.

Control variables in models included gender, age group, CEM weights, base admit count, and disease status for CAD, HF, diabetes, COPD, asthma, depression, chronic kidney disease, end stage renal disease, and cancer.

Independent variables of all models included gender (male/female), family structure (intact/non-intact), age, education (higher education/no higher education), ethnicity (Norwegian/non-Norwegian origin), PTSR and HSCL-8.

In a logistic regression model including gender, intercurrent HH formation, intercurrent UV cabinet use, surgical unit traineeship and report of regular use of AHR, the hazard ratio for the intervention was 3.837 (IC 2.086 7.058).

An ANOVA model including gender, exposure to early trauma, and MAOA genotype as between-subjects factors showed significant MAOA×ETLE (F1,227 = 8.20, P = 0.005) and gender×MAOA×ETLE (F1,227 = 7.04, P = 0.009) interaction effects.