R help - Nov 2023 - I need to create new variables based on two numeric variables and one dichotomize conditional category variables.

Just a minor point in the suggested solution:

df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG))

since WC and TG are not conditional, would this be a slight improvement?

df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58)))



-----Original Message-----
From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse
via
R-help
Sent: Friday, November 3, 2023 11:56 AM
To: r-help at r-project.org; mkzaman.m at gmail.com
Subject: Re: [R] I need to create new variables based on two numeric
variables and one dichotomize conditional category variables.

df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG))

That will do both calculations and merge the two vectors appropriately. It
will use extra memory, but it should be much faster than a 'for' loop.

Regards,
Jorgen Harmse.

------------------------------

Message: 8
Date: Fri, 3 Nov 2023 11:10:49 +1030
From: "Md. Kamruzzaman" <mkzaman.m at gmail.com>
To: r-help at r-project.org
Subject: [R] I need to create new variables based on two numeric
        variables and one dichotomize conditional category variables.
Message-ID:
        <CAGbxoeGjsxZKQ6qijEMq-X-5doqnQQS1jjPDDrGT6hH5xWqOKQ at
mail.gmail.com>
Content-Type: text/plain; charset="utf-8"

Hello Everyone,
I have three variables: Waist circumference (WC), serum triglyceride (TG)
level and gender. Waist circumference and serum triglyceride is numeric and
gender (male and female) is categorical. From these three variables, I want
to calculate the "Lipid Accumulation Product (LAP) Index". 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?

Your cooperation will be highly appreciated.

Thanks in advance.

With Regards

*--------------------------------*

*Md Kamruzzaman*

*PhD **Research Fellow (**Medicine**)*
Discipline of Medicine and Centre of Research Excellence in Translating
Nutritional Science to Good Health
Adelaide Medical School | Faculty of Health and Medical Sciences
The University of Adelaide
Adelaide SA 5005

        [[alternative HTML version deleted]]



	[[alternative HTML version deleted]]

______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Yes, that will halve the number of multiplications.

If you?re looking for such optimisations then you can also consider
ifelse(G=='male', 65L, 58L). That will definitely use less time &
memory if WC is integer, but the trade-offs are more complicated if WC is
floating point.

Regards,
Jorgen Harmse.



From: avi.e.gross at gmail.com <avi.e.gross at gmail.com>
Date: Friday, November 3, 2023 at 16:12
To: Jorgen Harmse <JHarmse at roku.com>, r-help at r-project.org
<r-help at r-project.org>, mkzaman.m at gmail.com <mkzaman.m at
gmail.com>
Subject: [EXTERNAL] RE: [R] I need to create new variables based on two numeric
variables and one dichotomize conditional category variables.
Just a minor point in the suggested solution:

df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG))

since WC and TG are not conditional, would this be a slight improvement?

df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58)))



-----Original Message-----
From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse
via
R-help
Sent: Friday, November 3, 2023 11:56 AM
To: r-help at r-project.org; mkzaman.m at gmail.com
Subject: Re: [R] I need to create new variables based on two numeric
variables and one dichotomize conditional category variables.

df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG))

That will do both calculations and merge the two vectors appropriately. It
will use extra memory, but it should be much faster than a 'for' loop.

Regards,
Jorgen Harmse.

------------------------------

Message: 8
Date: Fri, 3 Nov 2023 11:10:49 +1030
From: "Md. Kamruzzaman" <mkzaman.m at gmail.com>
To: r-help at r-project.org
Subject: [R] I need to create new variables based on two numeric
        variables and one dichotomize conditional category variables.
Message-ID:
        <CAGbxoeGjsxZKQ6qijEMq-X-5doqnQQS1jjPDDrGT6hH5xWqOKQ at
mail.gmail.com>
Content-Type: text/plain; charset="utf-8"

Hello Everyone,
I have three variables: Waist circumference (WC), serum triglyceride (TG)
level and gender. Waist circumference and serum triglyceride is numeric and
gender (male and female) is categorical. From these three variables, I want
to calculate the "Lipid Accumulation Product (LAP) Index". 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?

Your cooperation will be highly appreciated.

Thanks in advance.

With Regards

*--------------------------------*

*Md Kamruzzaman*

*PhD **Research Fellow (**Medicine**)*
Discipline of Medicine and Centre of Research Excellence in Translating
Nutritional Science to Good Health
Adelaide Medical School | Faculty of Health and Medical Sciences
The University of Adelaide
Adelaide SA 5005

        [[alternative HTML version deleted]]



        [[alternative HTML version deleted]]

______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

	[[alternative HTML version deleted]]

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?
>
>
	[[alternative HTML version deleted]]