Binary logistic regression: Multivariate binary logistic regression (vid 2 of 3)

This video discusses binary logistic regression models with more than one explanatory variable. It also introduces principles of model selection, including the use of Wald-tests and likelihood ratio tests.
This video is part of the NCRM Online Resource by Dr Heini Väisänen on Binary logistic regression. To see the whole resource visit www.ncrm.ac.uk/resources/online/
Please note: we may be unable to respond to individual questions on this video.
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[@davidheslop7632]

Excellent and clear example. Will use for my Public Health students who find this quite confusing. The final section on LL and selection of model complexity is VERY useful.

[@edwinicq]

So helpful, there's so little resources online on multiple logistic regression

[@drstaphylococcus]

👋🏽👋🏽👋🏽👋🏽 wonderful!

[@raishafathima3204]

Thank you for sharing, it's wonderfully explained. I would like to ask, in the probability equation, the value of having 2 children is -0.056. Isn't it supposed to be -0.06?

[@manuelleitner1996]

Hey, yes, I think she just rounded the result in the table to -0.06, but in reality it is -0.056, which is why she used this value for the equation.

[@lukwagoraymond1262]

The link for the NCRM online resources for this topic is unavailable. Is there an alternative link

[@NCRMUK]

Thank you for the message. The link in this video description should now be working. The NCRM website was temporarily offline for a few days at the end of December 2021, while maintenance work was carried out, but the website is now back online.

[@Debkah]

I'm confused ,is it called Multivariate or Multivariable ?

[@epi6321]

Two research articles breaking down the difference between the two: www.ncbi.nlm.nih.gov/pmc/articles/PMC3518362/ academic.oup.com/ntr/article/23/8/1446/5812038 Quick synopsis: Multivariate = more than 1 outcome (more than one dependent variable); Multivariable = one outcome (one dependent variable)