Diallel 6x6
grover.diallel.Rd
Diallel 6x6 in 4 blocks.
Usage
data("grover.diallel")
Format
A data frame with 144 observations on the following 5 variables.
yield
yield value
rep
a character vector
parent1
a character vector
parent2
a character vector
cross
a character vector
Details
Yield for a 6x6 diallel with 4 reps.
Note: The mean for the 2x2 cross is slightly different than Grover p. 252. There appears to be an unknown error in the one of the 4 reps in the data on page 250.
Source
Grover, Deepak & Lajpat Rai (2010). Experimental Designing And Data Analysis In Agriculture And Biology. Agrotech Publishing Academy. Page 85. https://archive.org/details/expldesnanddatanalinagblg00023
Examples
if (FALSE) { # \dontrun{
data(grover.diallel)
dat <- grover.diallel
anova(aov(yield ~ rep + cross, data=dat))
# These effects match the GCA and SCA values in Grover table 3, page 253.
libs(lmDiallel)
m2 <- lm.diallel(yield ~ parent1 + parent2, Block=rep,
data=dat, fct="GRIFFING1")
library(multcomp)
summary( glht(linfct=diallel.eff(m2), test=adjusted(type="none")) )
## Linear Hypotheses:
## Estimate Std. Error t value Pr(>|t|)
## Intercept == 0 93.0774 0.9050 102.851 <0.01 ***
## g_P1 == 0 1.4851 1.4309 1.038 1.0000
## g_P2 == 0 -0.9911 1.4309 -0.693 1.0000
## g_P3 == 0 2.2631 1.4309 1.582 0.9748
## g_P4 == 0 5.4247 1.4309 3.791 0.0302 *
## g_P5 == 0 -4.2490 1.4309 -2.969 0.1972
## g_P6 == 0 -3.9328 1.4309 -2.748 0.3008
## ts_P1:P1 == 0 -10.4026 4.5249 -2.299 0.6014
## ts_P1:P2 == 0 -9.7214 3.2629 -2.979 0.1933
## ts_P1:P3 == 0 -0.4581 3.2629 -0.140 1.0000
## ts_P1:P4 == 0 17.0428 3.2629 5.223 <0.01 ***
## ts_P1:P5 == 0 25.4765 3.2629 7.808 <0.01 ***
## ts_P1:P6 == 0 -21.9372 3.2629 -6.723 <0.01 ***
## ts_P2:P1 == 0 -9.7214 3.2629 -2.979 0.1928
## ts_P2:P2 == 0 7.0899 4.5249 1.567 0.9773
} # }