Maximum likelihood methods use standard statistical methods to estimate sensitivity and specificity of multiple tests from a comparison of the results of multiple tests applied to the same individuals in multiple populations with different prevalence levels ([#_ENREF_9 Hui and Walter, 1980]<nowiki>; </nowiki>[#_ENREF_4 Enøe et al., 2000]<nowiki>; </nowiki>[#_ENREF_15 Pouillot et al., 2002]). Key assumptions for this approach are:
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Maximum likelihood methods use standard statistical methods to estimate sensitivity and specificity of multiple tests from a comparison of the results of multiple tests applied to the same individuals in multiple populations with different prevalence levels ([#9 Hui and Walter, 1980]; [#4 Enøe et al., 2000]; [#15 Pouillot et al., 2002]). Key assumptions for this approach are:
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Maximum likelihood estimation
Maximum likelihood methods use standard statistical methods to estimate sensitivity and specificity of multiple tests from a comparison of the results of multiple tests applied to the same individuals in multiple populations with different prevalence levels ([#9 Hui and Walter, 1980]; [#4 Enøe et al., 2000]; [#15 Pouillot et al., 2002]). Key assumptions for this approach are:
