SPSS tutorials for beginners PART 7 - Composing ROC-curves

In this SPSS tutorial you will learn how to make an ROC-curve in SPSS. This is part of validation of prediction models and will describe the discriminatory properties of your prediction model.
About me:
I am a registered clinical epidemiologist and working as a fellow in medical oncology in the Netherlands. I have published over 50 manuscripts and have received several large research grants. I am particularly interested in research in geriatric oncology and am a an active member of the International Society for Geriatric Oncology.
You can find more information about my work on my linkedin page:
www.linkedin.com/in/nienke-de-glas
And here is my full bibliography:
pubmed.ncbi.nlm.nih.gov/?term...
Disclaimer:
Views and opinions are my own. Examples from clinical research will always include either my own work, or previously published research. I will include references in the description box.

[@fidyaifah182]

thankyou it helps me so much

[@statisticsandscientificres7558]

The videos are so nice, focused and practical. Really thanks.

[@nienkedeglas_mdphd]

Thanks a lot for your kind words!

[@muhammedhadedy4570]

Very nice presentation as usual. Thank you so much for your great videos.

[@nienkedeglas_mdphd]

Thanks!!

[@lironladenheim2703]

Great explanation. Thank you!

[@samirmammeri4059]

Thanks for your excellent presentation.

[@kudretkeskin8071]

It was a nice presentation. I wish you could also demonstrate the calculation of probabilities of each individual patient on SPSS. Thank you.

[@nienkedeglas_mdphd]

Thanks for the suggestion! Will try to do that in a next video. For now: you can save the predicted probabilities when you build your own model (for example logistic regression) by using the "save" button within the logistic regression menu, and than click "save predicted probabilities". It will than be saved as a new variable within your dataset. Good luck!

[@snellikkal8798]

Thank you so much for sharing your valuable work

[@nienkedeglas_mdphd]

You are very welcome :)!

[@drsuhailsayed]

Excellent presentation Dr de Glas. I was hoping you can guide me regarding the method to calculate the concordance index concept (Harrell's c index) and the online prediction model development.

[@user-pf4xd2fn6k]

Thank you for the excellent presentation, I have som questions thoug: I have performed AUS-curves for 2 prediction models and want to present them nicely with CIs and p-value in the graf, can you show how to incorporate that in the graf? Also for showing differences between the models how is that done? and what is the name of that test?

[@janelinelunghar9352]

Can bmi consider as state variables n waist circumference or bp or whr as test variables? N how to arrive bmi cut off

[@asneelasheshlal6485]

How abouit area under the curve for line graphs?

[@malachydivinefavour8280]

Great presentation, thank you! One question though, what if one filters out the lost to followup in SPSS, will the ROC curve work?

[@asneelasheshlal6485]

How to caluculate area under curve? please help.

[@rawanabuzinadah3333]

Hi. Very useful video thanks. If the model have different risk thresholds for example i’m externally validate a model that have three risk thresholds(less than 15% low risk group), 15 -60% moderate and more than 60% high propability. Can i compute that in the roc curve??
Thank you

[@michaelpaxonjulien8962]

Wherevis the validation tutorial?