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Crude ORs for continuous variables were obtained by using simple logistic regression.
Univariate analysis was performed by using simple logistic regression for association between independent and outcome variables.
We calculated basic frequencies, as well as odds ratios (ORs) and 95% confidence intervals (CIs) by using simple logistic regression adjusted for household design effect.
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Univariate analyses of all items were undertaken, followed by bivariate analyses using simple logistic regression to examine the relationship between confidence and all other variables.
Risk factors for HIV-1 infection were analyzed using simple logistic regression, followed by Bayesian multiple logistic regression because of sparse data.
Univariate analysis was done for categorical data using simple logistic regression (SLR) with a p-value <0.05 considered statistically significant.
The association of factors related to EVD infections was performed using simple logistic regression, with the corresponding Odds Ratio.
Our first benchmark test for this 6-protein signature was done using Simple Logistic (SL) [14], perhaps the simplest classifier from the Weka software suite.
Risk factors will be analysed using simple logistic regression to generate odds ratios and p values.
First, the effect of putative covariates was assessed using simple logistic and linear regressions.
Associations of the continuous independent variables with the outcome variables will be reported using simple logistic regressions.
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