Dear R-help,
can you please post the following message to the r-nabble forum.
Thanks!
---------------------------------------------------------------------------------------------------------------------------------
Dear R users,
I have been attempting to carry out post-hoc tests on a split-plot design:
Model:
Yijkl = µ + Ci + ω(i)j + δ(ij) + Tk + CTik + ωT(i)jk + Pl + CPil + ωP(i)jl
+ TPkl + CTPikl + ωTP(i)jkl + Ɛ(ijkl)
I have successfully matched the appropriate degrees of freedom and mean
squares presented in the table below using aov().
*EMS Table:*
2
2
2
3
F
R
F
F
i
j
k
l
EMS
df
F(1,2)
Ci
0
2
2
3
δ2 + 6δ2δ + 6δ2ω + 12Φ(C)
1
ω(i)j
1
1
2
3
δ2 + 6δ2δ + 6δ2ω
2
δ(ij)
1
1
2
3
δ2 + 6δ2δ
0
F(1,2)
Tk
2
2
0
3
δ2 + 3δ2ωT + 12Φ(T)
1
F(1,2)
CTik
0
2
0
3
δ2 + 3δ2ωT + 6Φ(CT)
1
ωT(i)jk
1
1
0
3
δ2 + 3δ2ωT
2
F(2,4)
Pl
2
2
2
0
δ2 + 2δ2ωP + 8Φ(P)
2
F(2,4)
CPil
0
2
2
0
δ2 + 2δ2ωP + 4Φ(CP)
2
ωP(i)jl
1
1
2
0
δ2 + 2δ2ωP
4
F(2,4)
TPkl
2
2
0
0
δ2 + δ2ωTP + 4Φ(TP)
2
F(2,4)
CTPikl
0
2
0
0
δ2 + δ2ωTP + 2Φ(CTP)
2
ωTP(i)jkl
1
1
0
0
δ2 + δ2ωTP
4
Ɛ(ijkl)
1
1
1
1
δ2
0
Total
23
mod <- aov(Budburst ~ CO2*SoilTemp*Photoperiod +
Error(Greenhouse/(SoilTemp*Photoperiod)), data = data)
summary(mod)
Error: Greenhouse
Df Sum Sq Mean Sq F value Pr(>F)
CO2 1 1465.2 1465.2 38.81 0.0248
Residuals 2 75.5 37.8
Error: Greenhouse:SoilTemp
Df Sum Sq Mean Sq F value Pr(>F)
SoilTemp 1 238.00 238.00 80.57 0.0122
CO2:SoilTemp 1 145.70 145.70 49.32 0.0197
Residuals 2 5.91 2.95
Error: Greenhouse:Photoperiod
Df Sum Sq Mean Sq F value Pr(>F)
Photoperiod 2 986.9 493.4 6.965 0.0498
CO2:Photoperiod 2 0.2 0.1 0.001 0.9989
Residuals 4 283.4 70.8
Error: Greenhouse:SoilTemp:Photoperiod
Df Sum Sq Mean Sq
F value Pr(>F)
SoilTemp:Photoperiod 2 14.56 7.28
0.514 0.6330
CO2:SoilTemp:Photoperiod 2 186.31 93.15 6.576
0.0544
Residuals 4 56.67
14.17
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 216 2887 13.37
However, as neither TukeyHSD() nor glht() accept objects of class
“aovlist”, I cannot carry out the post-hoc tests. Is there any way to run a
post-hoc test on an object of class "aovlist"?
Alternatively, I tried modelling the data using lme() and lmer(), but the
problem is that I cannot match the appropriate degrees of freedom and mean
squares obtained from the above included expected mean squares table using
lme() or lmer().
Has anyone else encountered and overcome this issue?
Thanks in advance,
Md. Shah Newaz
Faculty of Natural Resources Management
Lakehead University
Thunder Bay, Ontario, Canada
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