Description Usage Arguments Value Author(s) Examples
The function implements analysis of augmented random block design. The function assumes that checks (controls) are replicated r times making complete blocks while other treatments (new treatments) are unreplicated. Once the desired block size is determined, the checks are completely randomized making complete blocks and remaining plots / experimental units are also completely randomized however new treatments are unreplicated.
1 | aug.rcb(dataframe, genotypes, block, yvar)
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dataframe |
Dataframe object with at least variable containing genotypes, blocks and one response variable to be analyzed |
genotypes |
Name of column consisting of genotype or treatments (use "nameofcolumn" format) |
block |
Name of column consisting of block (use "nameofblock" format) |
yvar |
Name of response variable column (use "yvar" format) |
A list consisting of the following items :
anova |
Analysis of variance object |
adjusted_values |
dataframe Table with raw and adjusted values |
se_check |
Difference between check means |
se_within |
Difference adjusted yield of two varitiesvarieties / entries in same block |
SE_siff |
Difference between two varieties / entries in different blocks |
se_geno |
Difference between two varieties /entries and a check mean |
Umesh R. Rosyara
1 2 3 4 5 6 7 8 9 10 11 | # Example
data(augblock)
out <- aug.rcb(dataframe = augblock, genotypes = "var", block = "blk", yvar = "gw")
out$anova # analysis of variance
out$adjusted_values # yield observed and expected value table
# calculation of means
stab <- aggregate( gw ~ var, data=augblock, FUN= mean)
hist(stab$gw, col = "cadetblue", xlab = "Grain Yield",
main = "Mean yields from Augmented Yield Trial")
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