[R] Multiple comparisons when interacction
Jorge Lampurlanes Castel
jlampur at eagrof.UdL.es
Fri Feb 16 11:37:40 CET 2007
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:
infile 'data.csv' delimiter=';' firstobs=2;
input year plot block treat yield;
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;
proc print data=tres;
var year _year treat _treat estimate stderr df tvalue probt;
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
- 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.
>> 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
> 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.
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