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Comparisons of the average transport time between study arms were carried using t-statistics.
No significant differences between study arms were observed in the degree of relief of all analysed symptoms.
Point estimates for each monitoring strategy are used, even if differences between study arms were not significant at P=0.05.
No differences between study arms were apparent for these four measures over the follow-up period, and there were no statistically significant associations between any of these measures and outcomes.
We did not find any significant difference in carriage density between subjects from full or partially vaccinated communities, contrasting with the findings in relation to the prevalence of VT carriage, in which differences between study arms were small but statistically significant in some of the comparisons [ 12].
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One possible reason for the difference in number of culture positive patients between study arms is that cultures were drawn and culture results obtained after randomization had been done.
The crossover between study arms was documented.
Furthermore contamination between study arms is unlikely given the more intensive nature of the intervention.
Comparisons of the rate of compliance with infection control precautions between study arms was carried out using χ test statistic.
Modeling differences between study arms is important in order to correct for potential imbalances within studies which could bias the results.
As shown in Table 2, the proportion of patients who tested HIV-positive between study arms was comparable (326 or 18.6% in the intervention clinics and 604 or 21.4% in the control sites, p = 0.147), as was the median age (28 years in intervention and 26 years in control clinics).
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