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All variables significantly associated with seropositivity at a probability threshold of ≤0.25 in the bivariate analyses were entered into the initial multivariate models.
Only those variables that displayed statistically significant associations in the bivariate analyses were entered stepwise.
Variables with p < 0.2 in the bivariate analyses were entered in multivariate lineary regression analyses.
Statistically significant variables in the bivariate analyses were entered into the multivariate model.
Variables yielding P values no greater than 0.20 in the bivariate analyses were entered into a multiple logistic regression model.
b Variables that were significant in bivariate analyses were entered as independent variables in the multilevel regression analysis.
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Variables that were significantly associated (p < 0.05) with either physical or mental HRQOL (PHS or MHS, respectively) in bivariate regression analyses were entered in the multivariate models.
All statistically significant (p ≤ 0.10) predictor variables from bivariate analyses were simultaneously entered into the model.
In model 1, all candidate variables from the bivariate analyses were simultaneously entered, with backward elimination of variables not statistically significant (p <0.05).
Variables identified as significantly associated with RHT in the bivariate analyses were then entered into a multivariate logistic regression model to determine the independent contribution of each factor to predict RHT.
Variables that, on bivariate analyses, were significantly associated with isolation (p < 0.05) were entered into a binary logistic regression model using backwards elimination [ 23].
More suggestions(13)
bivariate analyses were completed
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bivariate comparisons were entered
bivariate analyses were undertaken
bivariate analyses were followed
bivariate analyses were considered
bivariate analyses were carried
bivariate analyses were used
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