>From the output you've shown, Minitab and R give the same thing when you
ask
for the same thing. In Minitab,
> Source DF Seq SS Adj SS Adj MS F P
> sector 6 9.0605 2.9989 0.4998 1.21 0.297
> depth 1 34.2072 11.9973 11.9973 29.16 0.000
> sector*depth 6 1.5364 1.5364 0.2561 0.62 0.712
> Error 578 237.7830 237.7830 0.4114
> Total 591 282.5871
In R:
> Response: Expr1
> Df Sum Sq Mean Sq F value Pr(>F)
> sector 6 9.1 1.5 3.67 0.0014 **
> depth 1 34.2 34.2 83.15 <2e-16 ***
> sector:depth 6 1.5 0.3 0.62 0.7124
> Residuals 578 237.8 0.4
Note the R output matches the `Seq SS' in Minitab, because that's what R
says it does: sequential tests. By `Adj. SS' and associated tests, I guess
Minitab meant `adjusting for other terms in the model'. If so, use drop1().
HTH,
Andy
> From: mrufino at cmima.csic.es
>
> Dear R list,
>
> I have been trying to do a linear model, extracting the effect of a
> covariate.... and the results do not match, when I do it with
> other programs
> (e.g. minitab).... so it is obvious that I was doing something wrong.
>
> Whan I do it with minitab, I have this results: (sector is a
> factor and depth
> is the covariate):
>
> Source DF Seq SS Adj SS Adj MS F P
> sector 6 9.0605 2.9989 0.4998 1.21 0.297
> depth 1 34.2072 11.9973 11.9973 29.16 0.000
> sector*depth 6 1.5364 1.5364 0.2561 0.62 0.712
> Error 578 237.7830 237.7830 0.4114
> Total 591 282.5871
>
>
> If I do with R, I have been trying everything it occurrs to
> me and looked
> everywhere and I could not obtain the same results and
> nothing is clear to
> me... (I am so sorry... probably it is lack of statistical knowledge):
>
> If I do:
> > anova(lm(Expr1~depth*sector))
> Analysis of Variance Table
>
> Response: Expr1
> Df Sum Sq Mean Sq F value Pr(>F)
> depth 1 38.2 38.2 92.76 <2e-16 ***
> sector 6 5.1 0.9 2.07 0.055 .
> depth:sector 6 1.5 0.3 0.62 0.712
> Residuals 578 237.8 0.4
>
> I am simply fitting a crossed anova, or because depth is
> continuos ... what is
> it doing?
>
> then, as it was not right, I went to look in the manuals, and in 'an
> introduction to R' states:
> y ~ A + x Single classification analysis of covariance model
> of y, with classes
> determined by A, and with covariate x. Is it like this?
> > anova(lm(Expr1~sector+depth)) #I don't think so...
>
> But I interpreted this as a additive model... and besides it
> did not work as
> well, so I tried what a friend recomended, i.e. x:z, whereas
> we are extacting
> the effect of x (covariate) on y... but it does not work as well...
> > anova(lm(Expr1~sector+depth+depth:sector)) # Would it be like this?
> Analysis of Variance Table
>
> Response: Expr1
> Df Sum Sq Mean Sq F value Pr(>F)
> sector 6 9.1 1.5 3.67 0.0014 **
> depth 1 34.2 34.2 83.15 <2e-16 ***
> sector:depth 6 1.5 0.3 0.62 0.7124
> Residuals 578 237.8 0.4
> -
> or like: anova(lm(Expr1~depth:depth*sector))
>
>
> I am lost... in the other times I just did with minitab, but
> I realy wanted to
> do it with R... can someone give me some lights?
> Is it very difficult to do it with R?
> Sorry for the long and messy email,
>
> thank you very much in advance,
> Marta
>
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