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 couldn’t 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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