[R] [EXTERNAL] Re: I need to create new variables based on two numeric variables and one dichotomize conditional category variables.

[Jorgen Harmse]

That�s ingenious, but I would hesitate to rely on a specific mapping between strings and integers. (I usually read data frames with stringsAsFactors=FALSE or coerce to character later: I don�t think it takes more memory.) Maybe create another column with the coefficients. What if gender is part of another formula?

Regards,
Jorgen Harmse.

From: CALUM POLWART <polc1410 using gmail.com>
Date: Saturday, November 4, 2023 at 18:23
To: avi.e.gross using gmail.com <avi.e.gross using gmail.com>
Cc: Jorgen Harmse <JHarmse using roku.com>, r-help using r-project.org <r-help using r-project.org>, mkzaman.m using gmail.com <mkzaman.m using gmail.com>
Subject: [EXTERNAL] Re: [R] I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
I might have factored the gender.

I'm not sure it would in any way be quicker.  But might be to some extent easier to develop variations of. And is sort of what factors should be doing...

# make dummy data
gender <- c("Male", "Female", "Male", "Female")
WC <- c(70,60,75,65)
TG <- c(0.9, 1.1, 1.2, 1.0)
myDf <- data.frame( gender, WC, TG )

# label a factor
myDf$GF <- factor(myDf$gender, labels= c("Male"=65, "Female"=58))

# do the maths
myDf$LAP <- (myDf$WC - as.numeric(myDf$GF))* myDf$TG

#show results
head(myDf)

gender WC  TG GF  LAP
1   Male 70 0.9 58 61.2
2 Female 60 1.1 65 64.9
3   Male 75 1.2 58 87.6
4 Female 65 1.0 65 64.0


(Reality: I'd have probably used case_when in tidy to create a new numeric column)




The equation to
calculate LAP is different for male and females. I am giving both equations
below.

LAP for male = (WC-65)*TG
LAP for female = (WC-58)*TG

My question is 'how can I calculate the LAP and create a single new column?

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