R help - Feb 2007 - Multiple comparisons when interacction]

Hello,

I send the message again with the data file as txt because it seems not to
be accepted as csv in the R-help list.

Data comes from a multiyear field experiment in which 4 levels of a
treatment (2, 3, 4, 6) are compared to see the effect on yield. It is a
randomized complete block design.

The SAS code follows:

options ls=95;
data uno;
        infile 'data.txt' delimiter=';' firstobs=2;
        input year plot block treat yield;
run;

proc mixed data=uno;
     class treat year block;
     model yield=block year treat treat*year;
     lsmeans year treat  /pdiff;
     lsmeans treat*year /slice=year pdiff;
     ods output diffs=dos;
run;

data tres;
      set dos;
      if year=_year;
proc print data=tres;
      var year _year treat _treat estimate stderr df tvalue probt;
run;

Data are attached as a file: data.csv.

In fact, I do not know if this is the best approach to analyze the data:

- Should block be considered as random? We use the same file and
randomization every year. We are interested in the long term effect of the
treatment.
- Data should be considered as repeated measurements over time (years)?

In multcomp package:

- What is the equivalence between the tests proposed  ("Sequen",
"AVE",
"Changepoint", "Williams", "Marcus",
"McDermott") and the tests agronomist
are used to do: LSD (least significant difference), Duncan multiple range
test, Scheffe, S-N-K (Student-Newman-Keuls)?


Thanks a lot for your interest.

Jorge Lampurlan?s
Agronomist

>> Is it possible to do this analysis in R?
>
> Yes, it is possible.  The syntax isn't in place yet.
>
> If you send me the complete SAS code and data for an example using slice,
> I will duplicate it for you in the multcomp package in R.  I will send
> that
> to the R-help list and to Torsten and it will bring us one step closer
> to the syntax.
>
> The example I showed before was designed to get the same answer as S-Plus
> multicomp using the adjust= argument.
>
> Rich
>
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