This data set contains boll retention of 10 cotton plants for 5 genotypes and 13 nodes. This data set can be analyzed in many ways: factorial factor design (genotype and position) or as split-plot design. For example, this data set can be analyzed by user-defined model as shown in the example.

1 |

A data frame with 338 observations on the following 5 variables.

`Year`

year of 2009

`Geno`

genotypes from 1 to 5

`Pos`

plant nodes from 5 to 17

`Rep`

field blocks from 1 to 4

`Brate`

mean boll retention for the first position over 10 plants

No other details are needed

No references or URLs available.

No reference available

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
library(minque)
data(brate)
head(brate)
brate$Geno=factor(brate$Geno)
brate$Pos=factor(brate$Pos)
brate$Rep=factor(brate$Rep)
res=lmm(Brate~1|Geno*Pos+Rep,data=brate)
res[[1]]$Var
res[[1]]$FixedEffect
res[[1]]$RandomEffect
res=lmm.jack(Brate~1|Geno*Pos+Rep,data=brate,JacNum=10,JacRep=1,ALPHA=0.05)
res[[1]]$Var
res[[1]]$PVar
res[[1]]$FixedEffect
res[[1]]$RandomEffect
## end
``` |

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