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Table 1.

Subsamples defined by the combination of age groups and fever status and observed frequencies of each pattern of test results.

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Table 2.

Lower – – and upper – – bounds of a confidence level for a two-sided confidence interval – – for a proportion (, where is the number of successes) using different methods.

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Table 3.

Some measures for the selected models (under HCI).

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Table 4.

Bayesian estimates of prevalence, sensitivities, specificities and predictive values, given by posterior means and 95% credibility intervals – Mean [] – with non-informative priors, by age groups and fever status, using the models M3, M4 and M5.

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Table 5.

Some information based on literature – RDT (ICT Diagnostics, Cape Town, South Africa).

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Table 6.

Coefficients and theoretical quantiles () of Beta distributions for sensitivities () and specificities (): a skeptical, a optimistic and our prior beliefs distribution.

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Table 7.

Bayesian estimates of the malaria infection prevalence, sensitivities, specificities and predictive values, given by posterior means and 95% HPD intervals - Mean [95% HPD] - by age groups and fever status, using skeptical, optimistic and our prior distributions to M5.

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Table 8.

Point estimates and 95% confidence intervals, though five different methods, for the sensitivity and the specificity of RDT in each subpopulation ( and ) and overall ( and ), using microscopy as a gold standard.

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