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In logistic regression models, the multivariate odds ratios (ORs) of invasive breast cancer for women in the highest tertile of circulating FT compared with the lowest was 2.43 (95% confidence interval (95% CI), 1.15 to 5.10; Ptrend = 0.03), whereas for total testosterone, the association had the same direction but was not statistically significant (OR, 1.27; 95% CI, 0.62 to 2.61; Ptrend = 0.51).
Except the obvious and strong association existing between BMI and dieting (overweight and obese children being more motivated to take on a diet than the normal weight group), that we used as confounding factor in our models, the multivariate analysis suggested that both, gender and self-esteem play a great role in dieting.
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If a study provided multiple models, the multivariate-adjusted model, which included all the potential confounding variables in the study, was selected.
In this study, we compared reaction norm and factor analytic models with the multivariate model without selection bias correction.
Compared with the crude model, the multivariate model produced similar risk estimates.
Guided by our conceptual model, the multivariate analysis has been conducted in several model steps.
Obesity was found to have a protective effect against cognitive decline in both the univariate model and the multivariate model.
The final model of the multivariate ANCOVA (Model 1) is displayed in Table 1.
The vector autoregressive (VAR) model (Christopher 1980) generalizes the univariate autoregressive model to the multivariate case.
Table 6 shows the final model of the multivariate analysis for children living in urban areas.
Once the univariate model was selected, the multivariate models including external regressors could be elaborated.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com