Hi all,
I analysed my data with lme and after that I spent a lot of time for
mean separation of treatments (post hoc). But still I couldnât make
through it. This is my data set and R scripts I tried.
replication fertilizer variety plot height
1 level1 var1 1504 52
1 level1 var3 1506 59
1 level1 var4 1509 54
1 level1 var2 1510 48
2 level1 var1 2604 47
2 level1 var4 2606 51
2 level1 var3 2607 55
2 level1 var2 2609 44
3 level1 var2 3401 46
3 level1 var3 3402 64
3 level1 var4 3403 64
3 level1 var1 3404 50
1 level2 var3 1601 59
1 level2 var1 1605 56
1 level2 var2 1610 53
1 level2 var4 1611 53
2 level2 var2 2403 56
2 level2 var1 2405 61
2 level2 var4 2407 69
2 level2 var3 2413 70
3 level2 var3 3508 67
3 level2 var4 3511 73
3 level2 var2 3512 62
3 level2 var1 3513 67
1 level3 var4 1406 77
1 level3 var3 1408 74
1 level3 var1 1409 71
1 level3 var2 1410 69
2 level3 var4 2501 62
2 level3 var3 2507 58
2 level3 var2 2508 56
2 level3 var1 2513 63
3 level3 var3 3601 73
3 level3 var2 3603 59
3 level3 var1 3609 56
3 level3 var4 3612 61
modela<-lme(height~variety*fertilizer, random=~1|replication)
summary(modela)
anova(modela)
library(multcomp)
hgt <- glht(modela,linfct=mcp(fertilizer="Tukey"))
summary(hgt)
Any body can help me to proceed tukey (or lsd) with lme that would be highly
appreciated.
Prabhath
University of Saskatchewan
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