grover.diallel.Rd
Diallel 6x6 in 4 blocks.
data("grover.diallel")
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
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.
Grover, Deepak & Lajpat Rai (2010). Experimental Designing And Data Analysis In Agriculture And Biology. Agrotech Publishing Academy. Page 85. https://archive.org/details/expldesnanddatanalinagblg00023
None
# \dontrun{
data(grover.diallel)
dat <- grover.diallel
anova(aov(yield ~ rep + cross, data=dat))
#> Analysis of Variance Table
#>
#> Response: yield
#> Df Sum Sq Mean Sq F value Pr(>F)
#> rep 3 2034 677.86 5.7478 0.001113 **
#> cross 35 32773 936.38 7.9399 < 2.2e-16 ***
#> Residuals 105 12383 117.93
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# These effects match the GCA and SCA values in Grover table 3, page 253.
library(lmDiallel)
m2 <- lm.diallel(yield ~ parent1 + parent2, Block=rep,
data=dat, fct="GRIFFING1")
library(multcomp)
#> Loading required package: mvtnorm
#> Loading required package: survival
#>
#> Attaching package: 'survival'
#> The following object is masked from 'package:asreml':
#>
#> rats
#> Loading required package: TH.data
#>
#> Attaching package: 'TH.data'
#> The following object is masked from 'package:MASS':
#>
#> geyser
summary( glht(linfct=diallel.eff(m2), test=adjusted(type="none")) )
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#> Warning: Completion with error > abseps
#>
#> Simultaneous Tests for General Linear Hypotheses
#>
#> 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 0.9749
#> g_P4 == 0 5.4247 1.4309 3.791 0.0303 *
#> g_P5 == 0 -4.2490 1.4309 -2.969 0.1970
#> g_P6 == 0 -3.9328 1.4309 -2.748 0.3000
#> ts_P1:P1 == 0 -10.4026 4.5249 -2.299 0.6025
#> ts_P1:P2 == 0 -9.7214 3.2629 -2.979 0.1931
#> 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 0.1925
#> ts_P2:P2 == 0 7.0899 4.5249 1.567 0.9772
#> ts_P2:P3 == 0 13.7157 3.2629 4.203 0.0110 *
#> ts_P2:P4 == 0 -8.7710 3.2629 -2.688 0.3351
#> ts_P2:P5 == 0 13.5728 3.2629 4.160 0.0124 *
#> ts_P2:P6 == 0 -15.8860 3.2629 -4.869 <0.01 **
#> ts_P3:P1 == 0 -0.4581 3.2629 -0.140 1.0000
#> ts_P3:P2 == 0 13.7157 3.2629 4.203 0.0108 *
#> ts_P3:P3 == 0 -23.5335 4.5249 -5.201 <0.01 ***
#> ts_P3:P4 == 0 1.2699 3.2629 0.389 1.0000
#> ts_P3:P5 == 0 0.1836 3.2629 0.056 1.0000
#> ts_P3:P6 == 0 8.8224 3.2629 2.704 0.3256
#> ts_P4:P1 == 0 17.0428 3.2629 5.223 <0.01 ***
#> ts_P4:P2 == 0 -8.7710 3.2629 -2.688 0.3352
#> ts_P4:P3 == 0 1.2699 3.2629 0.389 1.0000
#> ts_P4:P4 == 0 -12.2868 4.5249 -2.715 0.3193
#> ts_P4:P5 == 0 -9.9156 3.2629 -3.039 0.1707
#> ts_P4:P6 == 0 12.6607 3.2629 3.880 0.0245 *
#> ts_P5:P1 == 0 25.4765 3.2629 7.808 <0.01 ***
#> ts_P5:P2 == 0 13.5728 3.2629 4.160 0.0123 *
#> ts_P5:P3 == 0 0.1836 3.2629 0.056 1.0000
#> ts_P5:P4 == 0 -9.9156 3.2629 -3.039 0.1705
#> ts_P5:P5 == 0 -30.4793 4.5249 -6.736 <0.01 ***
#> ts_P5:P6 == 0 1.1619 3.2629 0.356 1.0000
#> ts_P6:P1 == 0 -21.9372 3.2629 -6.723 <0.01 ***
#> ts_P6:P2 == 0 -15.8860 3.2629 -4.869 <0.01 **
#> ts_P6:P3 == 0 8.8224 3.2629 2.704 0.3259
#> ts_P6:P4 == 0 12.6607 3.2629 3.880 0.0244 *
#> ts_P6:P5 == 0 1.1619 3.2629 0.356 1.0000
#> ts_P6:P6 == 0 15.1782 4.5249 3.354 0.0851 .
#> r_P1:P2 == 0 3.1600 3.8395 0.823 1.0000
#> r_P1:P3 == 0 -5.8625 3.8395 -1.527 0.9831
#> r_P1:P4 == 0 -2.0850 3.8395 -0.543 1.0000
#> r_P1:P5 == 0 4.5000 3.8395 1.172 0.9996
#> r_P1:P6 == 0 -0.1425 3.8395 -0.037 1.0000
#> r_P2:P1 == 0 -3.1600 3.8395 -0.823 1.0000
#> r_P2:P3 == 0 3.5100 3.8395 0.914 1.0000
#> r_P2:P4 == 0 -0.5700 3.8395 -0.148 1.0000
#> r_P2:P5 == 0 -1.4800 3.8395 -0.385 1.0000
#> r_P2:P6 == 0 0.9725 3.8395 0.253 1.0000
#> r_P3:P1 == 0 5.8625 3.8395 1.527 0.9832
#> r_P3:P2 == 0 -3.5100 3.8395 -0.914 1.0000
#> r_P3:P4 == 0 -0.6400 3.8395 -0.167 1.0000
#> r_P3:P5 == 0 3.0100 3.8395 0.784 1.0000
#> r_P3:P6 == 0 0.6550 3.8395 0.171 1.0000
#> r_P4:P1 == 0 2.0850 3.8395 0.543 1.0000
#> r_P4:P2 == 0 0.5700 3.8395 0.148 1.0000
#> r_P4:P3 == 0 0.6400 3.8395 0.167 1.0000
#> r_P4:P5 == 0 0.9475 3.8395 0.247 1.0000
#> r_P4:P6 == 0 -1.4350 3.8395 -0.374 1.0000
#> r_P5:P1 == 0 -4.5000 3.8395 -1.172 0.9996
#> r_P5:P2 == 0 1.4800 3.8395 0.385 1.0000
#> r_P5:P3 == 0 -3.0100 3.8395 -0.784 1.0000
#> r_P5:P4 == 0 -0.9475 3.8395 -0.247 1.0000
#> r_P5:P6 == 0 -1.9075 3.8395 -0.497 1.0000
#> r_P6:P1 == 0 0.1425 3.8395 0.037 1.0000
#> r_P6:P2 == 0 -0.9725 3.8395 -0.253 1.0000
#> r_P6:P3 == 0 -0.6550 3.8395 -0.171 1.0000
#> r_P6:P4 == 0 1.4350 3.8395 0.374 1.0000
#> r_P6:P5 == 0 1.9075 3.8395 0.497 1.0000
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> (Adjusted p values reported -- single-step method)
#>
## 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
# }