Binary Logistic Regression: Part 4 - Interpreting output (PAC and category significance)

[@fannyasangonoobamaoyana3285]

after 7 years and here I am. this video really helps me a lot. Thanks for your good explenation.

[@aghnialayalia2720]

Every single part of you binary logistic regression video really helps me a lot. I finally would be able to finish my thesis in peace. Keep up the good work.

[@khushbugandhi4828]

Very well explained in series format. easy and clear wording with time given to understand the interpretation.

[@adventureswithphi405]

This is really helpful. Thank you.

[@priyankakhuda7727]

Thank you very much. Excellent explaination.

[@sadeqhayder8965]

thank you very much sir it’s really helpful

[@stavroscheristanidis742]

excellent video, I have a question - how can i calculate the CI of constant in variables in the equation table?

[@Krishnaghy]

Very nicely explained. Ty. Could you explain how to generate OR and CI in ordinal regression using OMS cont panel.

[@fatemehesfahanian2683]

Thanks for your good explenatiom. i have a q. as in your video, the categorical variable ( i.e, education here) had 4 values but in the result the regression gave us 3 variable. what should we do about the last missed value?

[@osadeoboh9722]

Thank you for the insights. You said individuals with high school education were more likely to be in the NO category for the dependent variable i.e less successful. when the p value was less than 0.01 and the exp(B) was 0, please explain how this is so?

[@sintayehufekadu5979]

Thank you very much for your very clear presentation. Really helpful. I have some question, in your video part four when you interprete odds ratio, how it could be the odds ratio become 'zero' in reference category? I expect 1

[@spssisfun2270]

Hello Sintayehu. The odds ratio is not 1, because the odds ratio is with respect to something else. In this case, the base case, so the base case itself has no odds ratio (it is blank).

[@DanielaRodriguez-qw5dy]

Thank you so much for the information, it is more than clear. Nevertheless, I want to make sure if EXP (B) is medium (0.556) and my p-value over 0.05 then the model is not effective, and the independent value can not predict the dependent value?

[@temesgenmulugeta4222]

can I code all categorical variables as indicator like "first "for all? what is the importance of the last graph predicted probabilities for ----? what can I do if the H-L test's p value is less than 0.05?

[@aartichaudhary3306]

hello sir, sir how do we do mediation analysis in logistic analysis, please make one video on this topic

[@linetmutongi1308]

My binary regression analysis did not come up with the last table of case with list b. What could be the problem?

[@newgeneration8390]

confidence interval after Exp(B) was not clear, if its 8 in case of education to PG level, then what is the meaning of 1 to 32 in that interval ? and give me a hug with the perfect video you made, let me say, you are a genuis

[@christinacox43]

I am running two binary logistic regressions. In one, all of my IV's are significant in "Variables in the Equation" but my overall percentage in Block 0 is 65.0 and my overall percentage in Block 1 is 66.2. How do i interpret this sine all of my variables are apparently significant predictors but my model is only increasing by 1.2%? Also, in another analysis, all but two of my IV's are significant but my overall percentage in Block 0 is 70.9 and my overall percentage in Block 1 is also 70.9. How might I explain this?

[@josephkamaloni4875]

are these two binary regressions in a single study? what could be the reason for running two?

[@adanemekonnen5645]

Nice video. I subscribed as a support.

[@andrealaneeddepsicologa2054]

What if it isn’t significant? What does it mean if it is above 0.05? Mine is 0.76. Can I still consider it?

[@mimas2014]

As far as I know if it is bigger than 0,05 than it is statistically insignificant and it is not going to be considered in your interpretation.

[@spssisfun2270]

Hi Andrea. For significance, it should be less than .05, by convention. This essentially means that we will be correct 95% of the time, or that 95% of all possible values falls with in our confidence interval.

[@s.josephm.devanesan9977]

Dear Sir, This is S. Joseph from Chennai - India, Your video helped me, but I still have a doubt, in your video I could not find Crude Odds Ratio (COR) and Adjusted Odds Ratio (AOR). So, help me to understand. If the Exp(B) is AOR, where should I find the COR So, kindly help me underrated COR & AOR, With Regards…. 🙏

[@kellykelly6808]

how about ambition (1)? what is the pvalue for ambition ?

[@alexspeciale7748]

Why can I not see my odds ratio when there is more than 1 degree of freedom? How can I determine the odds ratio and CI for those cases?

[@ziaulislam87]

was your reference first or last?..be defualt its last option but your stating it as you selected first

[@sarasoleymani7803]

Hi, I have two odd results for my logistic regression. For one of my dependent varibale, the model is isgnificant but I don't have any significant predictor varibale. For my other dependent varibale, the model is insignificant and I have two significant predictor varbale. Could you help me that what can I do with these data and whether iti is possible or not?

[@shakeelasanauallah1763]

how interprete binary logistic regression..plzz upload in east wording...and complete idea about this

[@jessicajjsmith]

thank u for these vids

[@chyiyuh315]

Thank you =)

[@emmanuelsumari4187]

i like it

[@shakeelasanauallah1763]

easy wording