Add AUCs
- Thread starter Michael_svm
- Start date
- Tags area under the curve auc diagnostic roc
Lots of questions.
Area for under the curve is based on a threshold, did all studies have the same threshold or was the threshold based on a composite of variables?
Do you suspect heterogeneity between studies (random effects)? Was disease risk (prevalence) comparable?
Side note, I believe that I have read that the pooling of AUC values is not always recommended, many times people will focus on pooled sensitivities and specificities.
http://methods.cochrane.org/sites/methods.cochrane.org.sdt/files/public/uploads/MetaDAS%20Quick%20Reference%20v1.3%20May%202012.pdf
http://methods.cochrane.org/sites/m...blic/uploads/MetaDAS Readme v1.3 May 2012.pdf
Area for under the curve is based on a threshold, did all studies have the same threshold or was the threshold based on a composite of variables?
Do you suspect heterogeneity between studies (random effects)? Was disease risk (prevalence) comparable?
Side note, I believe that I have read that the pooling of AUC values is not always recommended, many times people will focus on pooled sensitivities and specificities.
http://methods.cochrane.org/sites/methods.cochrane.org.sdt/files/public/uploads/MetaDAS%20Quick%20Reference%20v1.3%20May%202012.pdf
http://methods.cochrane.org/sites/m...blic/uploads/MetaDAS Readme v1.3 May 2012.pdf
The receiver operator characteristic curve plots the sensitivity (y-axis) against 1-Specificity (x-axis) for a continuous variable. So yes it has all cut-offs for all continuous values in the dataset. Though, I have never seen a study make all that information available. You would have to have their raw datasets to do that. Most of the time studies present just the optimal cut-off value that maximized the AUC. If multiple studies do this, you may need to make sure they are all using the same cut-off (threshold) and that some of the study aren't controlling for other variables than others.