prevalence estimated from PCR results can be adjusted for the test sensitivity and specificity.
We have, however, additionally stated in the tables the threshold p values following a Bonferroni correction to adjust for the multiple tests for the readers interest.
Finner P-values were computed with WinPEPI software to adjust for the multiple outcomes tested [ 16].
Ideally, true prevalence should be estimated from apparent prevalence adjusting for the diagnostic test sensitivity and specificity [ 7].
Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure.
Permutation test with 100,000 replications was used to access the empirical significance adjusted for the number tests on multiple markers.
[13] In addition, we adjusted for the effects of test site, test lot, and technician.
To adjust for multiple testing, the Bonferroni-Holm method was applied to control for the familywise error rate.
To adjust for multiple testing, the false discovery rate (FDR) [LIT] was limited to 0.05.
In order to adjust for multiple testing, the level of significance was set at 0.01.
For both analyses, the Bonferroni method was adopted to adjust for multiple testing from the number of SNP loci detected.
