I am trying to do RCBD factorial analysis using 'doebioresearch' package. The anova is showing that the interaction effect is not significant. However, when compared the mean using Least Significance Test it is giving the different letters for the interaction (Cd*Si). Could you please explain why this is happening? Thanks a lot for helping. Below is the reprex:
mydata= data.frame(
stringsAsFactors = FALSE,
Replication = c(1L,1L,1L,1L,1L,
1L,1L,1L,1L,2L,2L,2L,2L,
2L,2L,2L,2L,2L,3L,3L,3L,3L,
3L,3L,3L,3L,3L),
Cd = c("Cd0","Cd0","Cd0",
"Cd10","Cd10","Cd10","Cd20",
"Cd20","Cd20","Cd0","Cd0",
"Cd0","Cd10","Cd10","Cd10","Cd20",
"Cd20","Cd20","Cd0","Cd0",
"Cd0","Cd10","Cd10","Cd10","Cd20",
"Cd20","Cd20"),
Si = c("SiNP0","SiNP0.5",
"SiNP1","SiNP0","SiNP0.5",
"SiNP1","SiNP0","SiNP0.5","SiNP1",
"SiNP0","SiNP0.5","SiNP1",
"SiNP0","SiNP0.5","SiNP1","SiNP0",
"SiNP0.5","SiNP1","SiNP0",
"SiNP0.5","SiNP1","SiNP0","SiNP0.5",
"SiNP1","SiNP0","SiNP0.5",
"SiNP1"),
Dry.wt = c(7.77,8.67,9.57,
5.64,6.97,8.73,2.53,5.79,6.9,
6.19,7.83,8.24,5.76,6.13,7.04,
3.78,5.44,6.25,7.46,8.21,
8.86,5.64,6.72,7.78,3.95,6.84,
6.95)
)
mydata
#> Replication Cd Si Dry.wt
#> 1 1 Cd0 SiNP0 7.77
#> 2 1 Cd0 SiNP0.5 8.67
#> 3 1 Cd0 SiNP1 9.57
#> 4 1 Cd10 SiNP0 5.64
#> 5 1 Cd10 SiNP0.5 6.97
#> 6 1 Cd10 SiNP1 8.73
#> 7 1 Cd20 SiNP0 2.53
#> 8 1 Cd20 SiNP0.5 5.79
#> 9 1 Cd20 SiNP1 6.90
#> 10 2 Cd0 SiNP0 6.19
#> 11 2 Cd0 SiNP0.5 7.83
#> 12 2 Cd0 SiNP1 8.24
#> 13 2 Cd10 SiNP0 5.76
#> 14 2 Cd10 SiNP0.5 6.13
#> 15 2 Cd10 SiNP1 7.04
#> 16 2 Cd20 SiNP0 3.78
#> 17 2 Cd20 SiNP0.5 5.44
#> 18 2 Cd20 SiNP1 6.25
#> 19 3 Cd0 SiNP0 7.46
#> 20 3 Cd0 SiNP0.5 8.21
#> 21 3 Cd0 SiNP1 8.86
#> 22 3 Cd10 SiNP0 5.64
#> 23 3 Cd10 SiNP0.5 6.72
#> 24 3 Cd10 SiNP1 7.78
#> 25 3 Cd20 SiNP0 3.95
#> 26 3 Cd20 SiNP0.5 6.84
#> 27 3 Cd20 SiNP1 6.95
attach(mydata)
library(doebioresearch)
RCBD2FLSD<-frbd2fact(mydata[4], Replication, Cd, Si, 1)
RCBD2FLSD