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| These [[attachment:posneglik.pdf | pdf slides]] indicate how to use specificity and sensitivity to obtain positive and negative likelihood ratios and rules of thumb to evaluate them to assess discrimination of the model. | Slide ten of these [[attachment:posneglik.pdf | pdf slides]] indicates rules of thumb for assessing positive and negative likelihood ratios to evaluate them to assess discrimination of the model. where Positive likelihood ratio = Sensitivity / (1 - Specificity) Negative likelihood ratio = (1 - Sensitivity) / Specificity The slides also briefly mention Hierarchical ROC curves which are useful for plotting curves combining within and between study variances from studies in meta-analyses. |
Positive and negative likelihood ratios
Slide ten of these pdf slides indicates rules of thumb for assessing positive and negative likelihood ratios to evaluate them to assess discrimination of the model.
where
Positive likelihood ratio = Sensitivity / (1 - Specificity)
Negative likelihood ratio = (1 - Sensitivity) / Specificity
The slides also briefly mention Hierarchical ROC curves which are useful for plotting curves combining within and between study variances from studies in meta-analyses.