Computes genotype-environment interaction means
ge_means(.data, env, gen, resp)
.data | The dataset containing the columns related to Environments, Genotypes, and the response variable(s). |
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env | The name of the column that contains the levels of the environments. |
gen | The name of the column that contains the levels of the genotypes. |
resp | The response variable(s). To analyze multiple variables at once,
a vector of variables may be used. For example |
A list where each element is the result for one variable containing:
ge_means: A two-way table with the means for genotypes (rows) and environments (columns).
gen_means: A tibble with the means for genotypes.
env_means: A tibble with the means for environments.
Tiago Olivoto tiagoolivoto@gmail.com
# \donttest{ library(metan) means_ge <- ge_means(data_ge, ENV, GEN, resp = everything()) # Genotype-environment interaction means get_model_data(means_ge)#>#>#> # A tibble: 140 x 4 #> ENV GEN GY HM #> <fct> <fct> <dbl> <dbl> #> 1 E1 G1 2.37 46.5 #> 2 E1 G10 1.97 46.9 #> 3 E1 G2 2.90 45.3 #> 4 E1 G3 2.89 45.9 #> 5 E1 G4 2.59 48.3 #> 6 E1 G5 2.19 49.9 #> 7 E1 G6 2.30 48.2 #> 8 E1 G7 2.77 47.4 #> 9 E1 G8 2.90 48.0 #> 10 E1 G9 2.33 47.7 #> # ... with 130 more rows#>#>#> # A tibble: 14 x 3 #> ENV GY HM #> <fct> <dbl> <dbl> #> 1 E1 2.52 47.4 #> 2 E10 2.18 44.3 #> 3 E11 1.37 54.2 #> 4 E12 1.61 49.6 #> 5 E13 2.91 46.6 #> 6 E14 1.78 41.0 #> 7 E2 3.18 44.1 #> 8 E3 4.06 52.9 #> 9 E4 3.68 50 #> 10 E5 3.91 52.2 #> 11 E6 2.66 45.9 #> 12 E7 1.99 48.5 #> 13 E8 2.54 45.2 #> 14 E9 3.06 51.3#>#>#> # A tibble: 10 x 3 #> GEN GY HM #> <fct> <dbl> <dbl> #> 1 G1 2.60 47.1 #> 2 G10 2.47 48.5 #> 3 G2 2.74 46.7 #> 4 G3 2.96 47.6 #> 5 G4 2.64 48.0 #> 6 G5 2.54 49.3 #> 7 G6 2.53 48.7 #> 8 G7 2.74 48.0 #> 9 G8 3.00 49.1 #> 10 G9 2.51 47.9# }