la(), which is from the plm package. It
would probably require substantial effort to get this to work.
Best,
John
> -Original Message-
> From: Miluji Sb [mailto:miluj...@gmail.com]
> Sent: Thursday, September 6, 2018 8:52 AM
> To: Fox, John
> Cc: r-help mailing list
>
Dear Ista,
Thanks for your reply. I tried both "prediction" and "margins" but neither
of them seem to work with plm.
Sincerely,
Milu
On Thu, Sep 6, 2018 at 3:04 PM Ista Zahn wrote:
> You might be interested in the "prediction" and "margins" packages.
>
> --Ista
>
> On Wed, Sep 5, 2018 at 6:3
You might be interested in the "prediction" and "margins" packages.
--Ista
On Wed, Sep 5, 2018 at 6:30 PM Miluji Sb wrote:
>
> Dear all,
>
> I am running the following panel regression;
>
> plm1 <- plm(formula = log(y) ~ x1 + I(x1^2) + heat*debt_dummy + tt, data =
> df, index=c("region","year"))
Dear John,
Apologies for not providing reproducible example. I just tried with a plm
example but ran into the same issue;
library(plm)
data("Produc", package = "plm")
zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc,
index = c("state","year"))
Ef.hd <- Effect(c("pc", "e
to answer your question.
Best,
John
> -Original Message-
> From: Miluji Sb [mailto:miluj...@gmail.com]
> Sent: Thursday, September 6, 2018 5:37 AM
> To: Fox, John
> Cc: r-help mailing list
> Subject: Re: [R] Marginal effects with plm
>
> Dear John,
>
>
I hope this helps,
> John
>
> --
> John Fox, Professor Emeritus
> McMaster University
> Hamilton, Ontario, Canada
> Web: socialsciences.mcmaster.ca/jfox/
>
>
>
> > -Original Message-
> > From: R-help [mailto:r-help-boun...@r-pro
r University
Hamilton, Ontario, Canada
Web: socialsciences.mcmaster.ca/jfox/
> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Miluji
> Sb
> Sent: Wednesday, September 5, 2018 6:30 PM
> To: r-help mailing list
> Subject: [R] Margin
Dear all,
I am running the following panel regression;
plm1 <- plm(formula = log(y) ~ x1 + I(x1^2) + heat*debt_dummy + tt, data =
df, index=c("region","year"))
where 'df' is a pdata.frame. I would like to obtain marginal effects of 'y'
for the variable 'x1'. I have tried the packages 'prediction
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