agridat (version 1.23)

grover.diallel: Diallel 6x6

Description

Diallel 6x6 in 4 blocks.

Usage

data("grover.diallel")

Format

A data frame with 144 observations on the following 5 variables.

yield

a numeric vector

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.

References

None

Examples

if (FALSE) {
  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    

}