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A bivariate analysis was based on Student's t test to compare continuous variables, including age, length of stay (LoS), and the EWS at −12, −24, and −72 h; χ2-square test was used to compare categorical variables.
Further, the choice of variables included in bivariate analysis was based on theoretical knowledge and statistical significance (P<0.05).
Initial univariate analysis was conducted to describe demographic variables (Appendix Table 1) Bivariate analysis was based on χ test (or Yates correction to the χ test where appropriate) of several potential predictors of RVFV seropositivity (Appendix Table 1) as well as bivariate comparisons between villages (Appendix Table 2).
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Bivariate and then multivariate analysis was based on the Mantel-Haenzsel procedure [ 24].
Decisions to include factors in the multiple logistic regression analysis were based on the strength of correlated factors (r < 0.75) or a P value <.05 on bivariate analyses.
Meta-analysis was based on the bivariate model in the presence of significant heterogeneity.
Because these predictions are based only on the FDR significant results, they are likely to be underestimates, a problem that the bivariate analysis was particularly sensitive to.
Bivariate analysis was done using the Chi Square test.
Bivariate analysis was performed using Pearson's correlation coefficients.
Bivariate analysis was performed with Pearson's linear correlation.
Next, a bivariate analysis was conducted of provider performance.
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