Logistic regression in R

[@EquitableEquations]

You can find materials supporting this vid (and others) at github.com/equitable-equations/youtube.

[@muqadasjaved7751]

Can you please do multivariate detrended fluctuations analysis or multifractal detrended fluctuations analysis in rstudio?

[@МаріяМуравйова]

omg thank you so much, I did almost the whole data analysis course at uni based on your videos😁 amazingly well explained and usable🙏

[@romanvasiura6705]

Amazing, thank you for this video lesson!

[@ahmedelkholy1323]

thanks a lot always adding something to me

[@weberb2781]

Hope you talk about the {fixest} package, it is very convenient to use this package for regression.

[@djprometheus923]

the GOAT

[@Ammarsays]

Is it necessary to convert binary response variable into "0" and "1". Mine is "Yes" and "No". Is there a better way to convert it?

[@EquitableEquations]

The response doesn't have to be 0 and 1, but it does have to be a factor with 2 levels. Probably as.factor() is your friend here.

[@flaviaoliveira5949]

what if there's more than 2 groups they can fall into?

[@EquitableEquations]

It's still possible to use logistic regression in that case (for instance with indicator variables), but in practice other techniques tend to be used instead.

[@badermuteb4552]

how did you simulate the data and load it as csv? sorry for the newbie question

[@EquitableEquations]

Hi! I'm planning on making vids about simulating data later in the year. You might start by googling "inverse CDF method". You can write a data set to a file with write_csv() and read it back with read_csv(), both from the {readr} package.

[@libbybendror]

your videos are the best! Any chance you will do MLM video please?

[@EquitableEquations]

Great suggestion!

[@daniellerobinson3688]

@@EquitableEquations I second this!! An MLM video would be exteremly useful.

[@leoniepfeifer4091]

Hi Thanks for the great video!!Do i need to mark the binary variable as binary? Because in R its recognized as "num"

[@romanvasiura6705]

Thank you!

[@EquitableEquations]

You got it, man!

[@AlbertoFCabreraCasillas]

Nice explanation of logistic regression. Even your intentional mistakes created learning opportunities. In a future follow up , may I suggest sharing with the viewer tips as to how to make meaning of the parameters (e.g., reporting log of odds)

[@EquitableEquations]

You read my mind! That's high on my list.

[@RomitGhosh-n6g]

Why do we write se = False

[@hannukoistinen5329]

But you don't do any testing, which is mandatory to give reliable results for your client!!!

[@EquitableEquations]

Nope this isn't complete in lots of ways.

[@FatGuyInALittleCoat1]

Good day! What if your GPA data was overwhelmingly skewed towards one of the binomial outcomes? Example: out of 100 total plot points, you had 98 plot points to the upper right hand part of your sigmoid line, all above a 3.0 GPA, and were admitted students. However, you had only one on the lower left sigmoid line that wasn’t admitted And more confusing….one that was admitted on the upper left of the graph with a low GPA. Those X variables would point towards a high probability of not getting admitted and that’s what the model would predict. How is this interpreted?

[@damirb6294]

interpretation of the results missing