Receiver Operator Characteristic (ROC) Curve in SPSS

This video demonstrates how to calculate and interpret a Receiver Operator Characteristic (ROC) Curve in SPSS. Evaluating sensitivity and specificity to inform selection of cutoff values is reviewed.

[newgeneration]

when it comes to regression analysis, there is not more strong lessons than this channels
thank you

[danielchong]

I needed a quick refresh of ROC curves and this is exactly what I was looking for! Thank you for the clear explanation of how to perform it on SPSS Todd.

[vikashsinghpatel]

This amazing video regarding ROC Curve, which I see, is the best video ever.

[bobbybelarmino]

Thank you Dr. Grande for easy to understand explanation!

[cassieperoulis]

I have never used a ROC curve so it was cool to learn about it, and why we use it. At first I was confused on what the depression score was used for but when I looked back at the beginning, you said it was the "scale" which cleared things up for me on that.

[sarahburrous]

This video really helped me understand the reasoning behind using ROC to check data. The details on sensitivity and specificity helped too.

[cardinalgrad]

Found this helpful when showing the difference between false negatives/positives and how they happen.

[newarknow]

Thank you so much! My course did not provide this very important information and expected me to be my own professor. I would not have understood any of my assignment if not for you.

[dmtv_]

Dear Dr Todd Grande. Thank you very much for your Youtube videos, especially on SPSS and mainly the ROC curve as they have helped me a lot. I am still struggling with how to generate a ROC table containing TP, TN, FP and FN given this(in this very video) particular form of ROC analysis where to predictor is set of continuous which performance and the cutoff for prediction of the "truth" are sought. Please how can I get SPSS to generate a ROC table containing TP, TN, FP and FN when doing ROC this way? Thank you.

[liakartika]

Thank you Dr. Todd.. I'm doing this analysis on prognostic test. My question is, can it continue with PPV, NPV, LR+, LR- I mean, with this numerical data? Or should we categorized first? thank you

[sihamballa]

i would like to thank you very much. i learned how to calculate specificity and sensitivity and the ROC..wonderful

[amlsalama]

Thank you very much for comprehensive simple way of explanation, Best regards

[MrAmanfasx]

Nicely explained. Learned what I really wanted to know.👍

[janelinelunghar]

very well explained. thank you Dr. Todd

[mustafamajidh]

thank you very much d. appreciate ur effort

[amandachaffin]

This answered my question about finding the area, if it is above .9 the test has great specificity and sensitivity. Above .8 is considered good as well. Good to know!

[hapvideolar]

Would it be better to choose optimum cut-off point over the likelihood ratio?

[Derokafela]

Best video ever created. Are there free versions of spss?

[Hkaus]

Dear Dr.Grande,

Thanks for your video!! clearly explained as always! This video only include one independent variable and I would like to ask what should I do if my project have to classify cancer recurrence and non-recurrence using multiple genes? should I use the binary logistic regression or the linear discriminant analysis or else? I hope I can receive your PROFESSIONAL advice!!!

[jamieong]

Thank you so much for the clear explanation, it is really helpful! If i want to choose my own cut-off scores to look at eg. 1.5 instead of 1.55 given by SPSS, how may i do so?