[R] Problem with lm

[isabelle Zabalza-Mezghani]

Hello Everybody,

I have a problem with the output of lm.
In fact, when I compare the R output and the Splus output, the results
appears to be different :

I have a dataframe with 5 factors , 16 rows and a response.
First, I tried to fit this response to a linear model :
lm(rep~(A+B+C+D+E),data).
The results beetween SPlus and R are different.

In a second time, I tried a new fit : lm(rep~(A+B+D+E+A:B),data).
The estimation of the main effects in the model are the same as the one
obtained for the first fit for Splus,
and are different for R.

Here an exemple :


On R:                            On Splus

        lm(rep~(A+B+C+D+E),data) ->  Intercept  12.6297
12.5573

A              0.0391                  0.0195

B            -0.0073                -0.0036

C              0.0443                   0.0221

D           -0.0321                 -0.016

E            -0.18887              -0.0944

    lm(rep~(A+B+D+E+A:B),data) ->  Intercept  12.7937
12.5573

A            -0.2445                  0.0195

B            -0.2910                -0.0036

D           -0.03213               -0.016

E           -0.18887               -0.0944

A:B          0.5672                  0.1418

Can someone explain what happens with these fitting procedure.

Thanks


Isabelle Zabalza-Mezghani





--
Isabelle Zabalza-Mezghani          Tel : 01 47 52 61 99
Institut Français du Pétrole       E-mail : isabelle.zabalza-mezghani at ifp.fr
1-4 Av. Bois Preau - Bat Lauriers
92852 Rueil Malmaison Cedex, France


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