Timeline for Post test probability with a ROC curve
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Mar 16, 2022 at 22:54 | comment | added | sethsh7 | Logistic regression which we have then calculated sensitivity, specificity and LR+/- at every threshold | |
| Mar 16, 2022 at 20:54 | comment | added | Daeyoung | What is the model for classification? How did you calculate sensitivity and specificity (there must be a classification rule to compute them)? | |
| Mar 16, 2022 at 20:52 | comment | added | sethsh7 | My model is genetic risk for a disease which is normally distributed in a population. At each threshold of the distribution, using the sensitivity and specificity I want to know how the prior probability (prevalence) is altered. We should expect that the prior probability falls below the median and increases above the median. But for a ROC curve the LR is always > 1 which is not helpful in this case. | |
| Mar 16, 2022 at 20:16 | comment | added | Daeyoung | Please elaborate on your problem and provide definitions. What is your model for this test? It's unclear how normally distributed data is converted to binary classification, and hence ends up computing a probability. | |
| S Mar 16, 2022 at 20:00 | review | First questions | |||
| Mar 16, 2022 at 20:01 | |||||
| S Mar 16, 2022 at 20:00 | history | asked | sethsh7 | CC BY-SA 4.0 |