Receiver Operating Characteristic (ROC) Curve Analysis for Optimal Cut-off in Disease Identification

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  • Опубликовано: 21 авг 2024

Комментарии • 41

  • @drfuzzy73
    @drfuzzy73 2 месяца назад +1

    Very well explained. Step-by-step and easy to understand. Thank you

  • @scienceupdates3606
    @scienceupdates3606 2 года назад +7

    One of the best demonstration of cut-off values on RUclips. 👍👍👍

  • @user-xe8mc3mb5s
    @user-xe8mc3mb5s 4 месяца назад +4

    This is the best explanation and I really appreciate this. It is just fantastic !!!!!!

  • @alinuh5564
    @alinuh5564 Год назад +1

    This is the best explanation of Co and ROC I came across
    Very good basic math and statistics foundation combined with good examples
    Many thanks

  • @vasu.12
    @vasu.12 Месяц назад

    Thank you so much. It's amazing. You saved my life..

  • @sheikhseerat7105
    @sheikhseerat7105 3 года назад +7

    Totally outstanding.....I can't explain...how much it helps me...thanks a lot.

    • @xanmos
      @xanmos  3 года назад +3

      You’re very welcome. I am glad to be of help :)

  • @oluchukwuokorie9064
    @oluchukwuokorie9064 9 месяцев назад

    Great explanation. 👍

  • @wasafisafi612
    @wasafisafi612 Год назад

    Thank you so much for this video. You help me a lot in writing my proposal. It is going to help me a lot in my project. May God bless you abundantly. Gracias

  • @samira7681
    @samira7681 Год назад

    thank you so much!! You explained this so clearly, understandably and thoroughly! thanks a lot

  • @nurbasirahghazali6904
    @nurbasirahghazali6904 3 года назад +1

    Thanks so much for the very clear explanation!

  • @chinnapeddakahanilu2024
    @chinnapeddakahanilu2024 3 года назад +1

    Superb and ultimate explanation. Thankyou

  • @alinuh5564
    @alinuh5564 Год назад

    Anyway it’s excellent to learn and understand underpinning knowledge in ROC and cut off determinations

  • @salahmarajan2120
    @salahmarajan2120 2 года назад +1

    Outstanding

  • @sujathadevi3958
    @sujathadevi3958 Год назад

    suberb explanation. thanks

  • @priyakulkarni9583
    @priyakulkarni9583 2 года назад +1

    Excellent

  • @sumaiyaarefen3608
    @sumaiyaarefen3608 2 года назад

    You are a gem

  • @shaman14302
    @shaman14302 3 года назад +2

    Are you a Filipino sir? Got curious with the accent hehe. This helped me a lot. Thank you!

    • @xanmos
      @xanmos  3 года назад +2

      yes po ☺️

  • @dickeSeekuh
    @dickeSeekuh 2 года назад +1

    Thank you very much for this great explanation!
    I wondered if there is a possibility to extract the information from the plot (roc-curve) into a table. So that i can see the sens and spec for all possibile cut-offs. I coudn't find anything about this in the r package handbook. Do you have an idea, how i could transform this into a table?

  • @NishantSewgobind
    @NishantSewgobind 8 месяцев назад +1

    Thanks for the video, nice explanation. Could you please explain why the values of J in ID's 19 and 20 are neglected? They have the highest J indices...

    • @NishantSewgobind
      @NishantSewgobind 8 месяцев назад

      I'm sorry I meant the J indices at 17:39 min. ID 19 has J = 0.798 and ID 20 has J = 0.909. Still, ID 12 with J = 0.616 is chosen as the cut off.

    • @xanmos
      @xanmos  8 месяцев назад +1

      ​@@NishantSewgobind Oh that one. In ID 19, Sens = 0.0909 and Spec = 0.889, so J index is 0.0901 + 0.889 - 1 = -0.02 (not 0.798), while for ID 20, Sens = 0.0909 + Spec = 1, so J index is 0.0909 (not 0.909) . Im sorry about that but i think there was a typo error on those two in the powerpoint i used. THANKS A LOT for raising that concern. I didn't see that. Nonetheless, the Max J index is still the one at ID 12, which J index is 0.616.

    • @NishantSewgobind
      @NishantSewgobind 8 месяцев назад

      @@xanmos aha! Thanks for the explanation, really appreciated 😄👍

  • @martinliptak1436
    @martinliptak1436 2 года назад +1

    Hello! This topic is quite far away from my specification so maybe I have stupid question. It’s about ECLIA test for Covid and the results are in COI, where COI1 is reactive and positive for antibodies. I just dont understand if the higher number tells me something about quantity of antibodies or no. Basically I’m just curious what that number tells. Brother was tested for Covid antibodies and his number is COI=11. Thanks for your answer.

    • @xanmos
      @xanmos  2 года назад +1

      I am not a medical laboratory scientist to answer ur question perfectly but as far as my readings are concerned (as to what i understood), yes the cutoff index (COI) indicates the amount of antibodies (specifically nucleocapsid) produced while patients have COVID-19. The nucleocapsid is at its peak on the first 12hrs of infection so maybe ur brother is at its early infection state when ELICA test was performed thats why it’s high to as much as 11.
      you may refer to these articles:
      mdpi-res.com/d_attachment/diagnostics/diagnostics-11-01808/article_deploy/diagnostics-11-01808.pdf
      www.rrh.org/documents/COVID-19-Ab-Fact-Sheet.pdf
      Thank u.

  • @alinuh5564
    @alinuh5564 Год назад

    Can i share that SPSS can now calculate younden’s index or J stat
    Used SPSS V29

    • @xanmos
      @xanmos  9 месяцев назад

      thank u. I just got spss trial version and yes, there’s youden index already 🥳

  • @wasafisafi612
    @wasafisafi612 Год назад

    could you demonstrate how to add two graph curve?

    • @xanmos
      @xanmos  Год назад

      It can be done using the pROC package in R or RStudio (not using optimalCutoff package). Thank you for watching and appreciating my work. :)

    • @wasafisafi612
      @wasafisafi612 Год назад

      Good day. I would like to ask for your help. If I want to calculate the sensitivity and specifity for a different cut-off point, how do you run it in R using the same package? Thank you for your help in advance

  • @haoduong6565
    @haoduong6565 Год назад

    Hi, you have example in Python? Thanks!

    • @xanmos
      @xanmos  Год назад +1

      Sorry i do not use Python.

    • @haoduong6565
      @haoduong6565 Год назад

      @@xanmos Hi, have you done simultaneously optimizing cut-points for more than 1 variable or joint dichotomization?

  • @linanaji6184
    @linanaji6184 2 года назад

    thank you so much , I was wondering if you have any idea how find these by Graphpad prism

    • @xanmos
      @xanmos  2 года назад +1

      Medcalc does this technique, but i think Graphpad does not.

    • @linanaji6184
      @linanaji6184 2 года назад

      @@xanmos thank you so much for the reply, could you please share a link to your video if you made just the section when you did it on the R program.

    • @xanmos
      @xanmos  2 года назад +1

      @@linanaji6184 in 25:22 of this video, I started demonstrating in R.

    • @linanaji6184
      @linanaji6184 2 года назад

      @@xanmos I cannot download the OptimalCutpoints pcakage

    • @xanmos
      @xanmos  2 года назад +1

      @@linanaji6184 once R is installed, just enter
      install.packages("OptimalCutpoints")
      followed by
      library(OptimalCutpoints)