Outstanding. Best explanation of logistic regression I've heard. I especially appreciated the frequent reminders/examples of what each equation/variable actually means. Excellent tone, too.
Thanks. Great teaching method/skill. Complicated concepts made easier with real life examples and discussion around practical applications. More excitement in the delivery than most teachers.
Thanks for this video! I've been looking for a good reference to refresh my memory on the basics of logistic regression, interpretations etc., and this is the best one that I've seen so far.
I found it - if we want to interpret the beta estimates of a nominal effect the same way as a continuous effect (i.e., e^estimate = OR), the "nominal" variable needs to be0 or 1 and changed to be a continuous variable. Otherwise, JMP treats it differently.
Thanks! Obviously with over 20 000 views your explanations are very appreciated. Any pointers on how to interpret the beta estimate when the independent variable is nominal?
At 32:22, when you show how to figure out odds ratio for c unit change (instead of a single unit, or the entire range), how do you calculate the 95% CI using this technique? thanks
This might be a stupid question, but I've got some trouble figuring out where those probabilities used in the odds still come from (the once denoted pi-hat). Regarding the probability of an outcome to the model. Would you first create a regular Linear probability model, with robust stanards, and use those for the (pi / 1 - pi) formula? (i.e the LPM gives you the pi values, and you'd use those in the logit?
Very interesting presentation - thanks. Does JMP recognize standard SAS code? Could you write some PROC LOGISTIC commands in a window or does it all have to be through this drag-drop GUI?
JMP has its own scripting language (JSL), so you would need jsl not sas code to execute a jmp analysis via code. JMP can run SAS code if you have a connection to a SAS server, but whatever you run is processed by the SAS server, not JMP. For the most part JMP is driven very effectivley via the GUI so it's not necessary to rely on JSL unless you're scripting for reproducibility or custom workflows.
Outstanding. Best explanation of logistic regression I've heard. I especially appreciated the frequent reminders/examples of what each equation/variable actually means. Excellent tone, too.
Thanks. Great teaching method/skill. Complicated concepts made easier with real life examples and discussion around practical applications. More excitement in the delivery than most teachers.
God bless you for these posts; a very satisfied PhD candidate from Winnipeg :)!!!
Sincerely grateful for you time and effort in putting this together. Effective and intuitive communication of often muddled information.
Thanks for this video! I've been looking for a good reference to refresh my memory on the basics of logistic regression, interpretations etc., and this is the best one that I've seen so far.
Very good, very clear exposition. Well done.
Thanks!!! another very satisfied PhD student from BC Why can't my teachers explain it so clearly :(
Excellent video! Extremely helpful. It helped me put a lot into perspective! Great job!
super helpful!!! wish you around when I took stats as an undergrad.
thank you so much from your help, i got more and more important how you explain,
thanks again and again
Thank you very much. I really do have a wonderful lecture. It will help me a great deal
Great video, very helpful and nicely explained, Thank you so much
I found it - if we want to interpret the beta estimates of a nominal effect the same way as a continuous effect (i.e., e^estimate = OR), the "nominal" variable needs to be0 or 1 and changed to be a continuous variable. Otherwise, JMP treats it differently.
This is great--really helpful! Thank you.
Thanks! Obviously with over 20 000 views your explanations are very appreciated.
Any pointers on how to interpret the beta estimate when the independent variable is nominal?
Thank you. very clear explanation.
THANK YOU, GREAT LECTURE
@mrpapparappa You're so welcome!
/surrender Wow, where did you learn all this? Great video. You should add your teaching information in the info box. I'd totally take this class.
Great demo for using JMP. Thank you. Can you tell me the name of the textbook you're using?
At 32:22, when you show how to figure out odds ratio for c unit change (instead of a single unit, or the entire range), how do you calculate the 95% CI using this technique? thanks
This might be a stupid question, but I've got some trouble figuring out where those probabilities used in the odds still come from (the once denoted pi-hat).
Regarding the probability of an outcome to the model. Would you first create a regular Linear probability model, with robust stanards, and use those for the (pi / 1 - pi) formula? (i.e the LPM gives you the pi values, and you'd use those in the logit?
@jojito29 My pleasure!
Very interesting presentation - thanks. Does JMP recognize standard SAS code? Could you write some PROC LOGISTIC commands in a window or does it all have to be through this drag-drop GUI?
JMP has its own scripting language (JSL), so you would need jsl not sas code to execute a jmp analysis via code. JMP can run SAS code if you have a connection to a SAS server, but whatever you run is processed by the SAS server, not JMP. For the most part JMP is driven very effectivley via the GUI so it's not necessary to rely on JSL unless you're scripting for reproducibility or custom workflows.
Thank you!! :)
Great!
Can you change the regressor unit from 1 unit to being 10 units
Try running R Studio
which software do use to get logistic regression?
Is this JMP Pro? Or basic JMP
You should do one for R as well. :)