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For all outcomes, sociodemographic variables with a P-value<0.2 in the bivariate analyses were entered into the multivariate model, then retained in the final model if P<0.05.
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The multivariate model is then assessed based on the Bayesian point and interval hypothesis testing approaches.
The multivariate model was then stratified by RRM1 (Table S2) and without disease stage.
Multivariate model was then constructed, including variables that showed an effect on the prediction of TB positivity in the univariate analyses at the p = 0.05 level of significance.
The final multivariate model was then used to model the probability of transmission for combinations of individual patient characteristics.
The multivariate model was then constructed with variables that had a univariate P value of 0.1 or less.
A multivariate model was then built jointly for all three groups to compare survival probabilities between populations.
All covariates were included in a multivariate model, and then only variables retaining significance (p < 0.05) were included in a reduced multivariate model.
The first multivariate model was then fitted by including scales/items that were found to have a statistically significant association with utility in univariate analysis (p < 0.1).
Factors in the univariate models with a P value < 0.20 were included in an initial multivariate model and then a backward elimination procedure was used to remove variables with a P value > 0.05.
Baseline demographic and clinical factors with P < 0.20 in the univariate model were included in an initial multivariate model and then a backward elimination procedure was used to remove variables with P > 0.05.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com