>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: [EMAIL PROTECTED] > > 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 > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
