Interpreting Odds Ratio with Two Independent Variables in Binary Logistic Regression using SPSS

This video demonstrates how to interpret the odds ratio (exponentiated beta) in a binary logistic regression using SPSS with two independent variables. A binary logistic regression returns the odds of belonging to a level of a dichotomous dependent variable using one or more independent variables.

[@abdullahshahzad6387]

I have been searching for a video explaining this for a lot of time now and finally landed here. You explained everything so beautifully. Thank you so much. You helped me in completing my thesis🙏

[@ScienceLongevity]

Very direct, simple and straight to the point. Very useful tips.

[@DrGrande]

Thank you -

[@yehiaelyamani6943]

Brilliant and lucid explanation. Many thanks

[@anilk1241]

please add a cursor, it is very difficult to follow what you are referring to (I am a beginner learner)

[@karilinden6210]

Excellent video, thank you! - Question: How to interpret for the independent continuing variable (“assessment”) the 95% CI including number 1 and Sig. 0.61 (>0.05)...? Exp(B) shows the Odds but this other information of its "probability"...?

[@marjanmansourvar5455]

A variable such as License should be in categorical or not? (I have the same variable and the results are different once I select the categorical with the one I didn't select that) thanks

[@briancroxford6981]

Love your videos man!

[@DrGrande]

Thank you so much -

[@manuelalevi6734]

Hi, could you explain me how to interpret the OR related to the CI? thank you so much for the video

[@roccos7642]

you lost me at 7:49....not sure where those numbers are coming from. Can you explain?

[@stephscro]

Do you have any resources for multiple logistic regression with categorical predictor variables that have more than 2 categories? Thank you!

[@arwaalderam6322]

thank you so much that was very helpful 🙏🙏

[@karilinden8219]

Excellent video, thank you! - Question: How to interpret for the continuing independent variable (now: 'Assessment') the 95% CI including value 1 and Sig. being >0.50 (now: 0.61)....? Illusrates the "probability" of Exp(B) odds ratio?

[@martau3]

Thank you for these very helpful videos :-). Can/should the Wald test be used to test for significance when performing binary logistic regression with data which I am treating as a population? I have been advised that inferential statistical tests are not appropriate with populations, so I'm confused whether to pay attention to the Wald test - particularly as it does not appear to have a straightforward relationship with the size of the coefficients/log odds. Thank you in advance for any answers!

[@sharmilasenguptachowdhry509]

Excellent explanation

[@ifteeable]

thanks for the video!
Q: what if the OR is less than 1 (for example 0.030) for Binary Independent variable (coded: 0-No, 1-Yes) for Binary Dependent Variable. How wold you interpret the results then?

[@newgeneration8390]

did you find your answer? if you found please reply here, I need that answer. I was reading comments if he replied, but he didn't.

[@bashiralee5464]

Thanks so much sir. This video was really helpful.

[@DrGrande]

You are quite welcome -

[@johnonugwu]

Can one do binary logistic regression if the variables have missing data

[@obsiebassia5129]

thank you so much , the video is very helpful. Can I use this model to predict probability if information on one of the independent variable is not given ? for example can I use this model to predict probability of admission if i don't have information on assessment but if the individual is licensed ? THANK YOU

[@ziaulislam87]

how do you know i the reference is licensed or unlicensed...there is an option of first and last selection in categorical variables ..does it automatically selects zero(unlicensed) as reference displays odd ratio for 1s(licensed)

[@ismaelgarcia4744]

Your video is interesting, but I have a question:
If I have only the Odds Ratio for a continuous variable, I have to interpret it as “for every point that the continuous variable increases, the odds will increase by the value of the Odds Ratio”?

[@anjunavk2839]

Yes. For every unitary increment in the continous variable, the odds increase by [1-exp(B)]

[@gayaneharutyunyan9186]

thanks a lot for video :D I'v performed a binary logitic regression
analysis with 2 independent (categorical) variables, the p valuse were
significant but OR ratio were less then 1, what migth be the reason ?
what does it mean please help me((

[@maryamilyas9244]

pata chala so plz share it

[@phine999]

thank you for your thorough step by step explanation, it was really helpful. Can the same interpretation be applied for binary logistic regression interaction analysis and results? If not, where can I find videos regarding the explanation on how to interpret logistic regression interaction analysis results?

[@YeoWeiXiong]

did u manage to find a video which indicates on how to interpret interaction analysis

[@phoenixquotes]

I really appreciate your educational videos and you hope you can answer the following question:
can we use stepwise logistic regression in case of dependant variable that is not normally distributed? if no there is an alternative?

[@DrGrande]

Logistic regression does not assume the dependent variable is normally distributed.

[@hridayamusings4445]

IS THIS THE ADJUSTED ODDS RATIO BECAUSE YOU INCLUDED MORE THAN 1 INDEPENDENT VARIABLE...PLZ ANSWER ME...I AM A BEGINNER.

[@vara76]

Hi...you are right. This is adjusted odds. The first step would include individual independent variables to give you crude odds.

[@binudorjee5388]

I am getting large odd value like 17, 18 etc, is it ok?

[@yehiaelyamani6943]

Statistically it is quite possible. It just shows that you are analyzing for something that is fairly obvious, such as the odds of diabetics having a high blood sugar value compared with non-diabetic subjects!

[@maryamilyas9244]

plz share it ... same here