The more general model for estimating structural models is lavaan,
contained in the package lavaan.
yaya bamba via R-help <r-help@r-project.org>
Sent by: "R-help" <r-help-boun...@r-project.org>
05/10/2018 12:01 PM
Please respond to
yaya bamba <bamba...@yahoo.fr>
To
"r-help@r-project.org" <r-help@r-project.org>, Michael Dewey
<li...@dewey.myzen.co.uk>,
cc
Subject
Re: [R] Mod�le � Equations structurelles
In my previous mail, I was asking help to fit structural equations models
by using Partial Least Square (PLS) approch.I have used package plspm. I
want to know how to manage moderating and mediating variables. I also want
to show simultanously the graph of internal model and measurement model.
Thks.
Le jeudi 10 mai 2018 � 15:42:46 UTC, Michael Dewey
<li...@dewey.myzen.co.uk> a �crit :
Dear Yaya
You will get more responses if you can post in English which is the
language of the list.
If you want advice about package choice you need to tell us what
packages you have considered and rejected. You would also benefit from
searching the CRAN Task Views - possibly the Psychometrics one might
help you. If you want someone to send you code, as appears from your
mail, you are out of luck on this list.
Michael
On 10/05/2018 15:50, yaya bamba via R-help wrote:
> Bonjour,
> Quelqu'un pourrait m'aider avec le code R pour estimer les mod�les �
�quations structurelles via l'approche PLS,int�grer des variables
mod�ratrices et m�diatrices et afficher les graphique simultan� des
mod�les interne et de mesure?
> Cdt.
> [[alternative HTML version deleted]]
>
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> and provide commented, minimal, self-contained, reproducible code.
>
--
Michael
http://www.dewey.myzen.co.uk/home.html
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______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide
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______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
