anova_joint | R Documentation |
Performs a joint analysis of variance to check for the presence of genotype-vs-environment interactions using both randomized complete block and alpha-lattice designs.
anova_joint(.data, env, gen, rep, resp, block = NULL, verbose = TRUE)
.data |
The dataset containing the columns related to Environments, Genotypes, replication/block and response variable(s). |
env |
The name of the column that contains the levels of the environments. The analysis of variance is computed for each level of this factor. |
gen |
The name of the column that contains the levels of the genotypes. |
rep |
The name of the column that contains the levels of the replications/blocks. |
resp |
The response variable(s). To analyze multiple variables in a
single procedure a vector of variables may be used. For example |
block |
Defaults to |
verbose |
Logical argument. If |
A list where each element is the result for one variable containing the following objects:
anova: The two-way ANOVA table
model: The model of class lm
.
augment: Information about each observation in the dataset. This
includes predicted values in the fitted
column, residuals in the
resid
column, standardized residuals in the stdres
column,
the diagonal of the 'hat' matrix in the hat
, and standard errors for
the fitted values in the se.fit
column.
details: A tibble with the following data: Ngen
, the
number of genotypes; OVmean
, the grand mean; Min
, the minimum
observed (returning the genotype and replication/block); Max
the
maximum observed, MinGEN
the loser winner genotype, MaxGEN
,
the winner genotype.
Tiago Olivoto tiagoolivoto@gmail.com
Patterson, H.D., and E.R. Williams. 1976. A new class of resolvable incomplete block designs. Biometrika 63:83-92.
get_model_data()
anova_ind()
library(metan) # traditional usage approach j_an <- anova_joint(data_ge, env = ENV, gen = GEN, rep = REP, resp = everything()) # Predicted values get_model_data(j_an) # Details get_model_data(j_an, "details")
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