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Missing data imputations will be performed on variables with high probability of missingness, either by discarding or replacing data with the mean of the observed values for that variable.
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Multivariate logistic regression analysis was performed on variables found to be significantly associated with mortality.
Results: Multivariate logistic regression analysis was performed on variables found to be significantly associated with mortality.
Analyses were performed on variables weighted by primary sampling units, strata and assigned weight for each PAR.
Multiple logistic regression analysis was performed on variables with an unadjusted effect and a p-value <0.10 on simple logistic regression analysis.
Multiple logistic regression analysis was performed on variables with an unadjusted effect and a P < 0.1 on simple logistic regression analysis.
Bivariate analysis was performed on variables likely to influence the prompt access to the ACT as well as the source of care.
Logarithmic transformation was performed on variables that were not normally distributed.
Analysis was performed on variables logarithmically transformed to enhance symmetry of measures.
Backward stepwise logistic regression analysis was performed on variables associated with P<0.20.
In phase 1, a stepwise logistic regression was performed on variables in group 1.
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