Experiment carried out in a vegetation house with
soybeans. The experiment has two plants by plot with three levels of
the factor amount of water in the soil (water)
and five levels of potassium fertilization (pot).
The plots were arranged in five blocks (block).
Three response variables are of the interest, namely, grain yield,
number of seeds and number of viable peas per plant.
The data set has 75 observations of 7 variables.
pot - Factor five levels of potassium fertilization.
water - Factor three levels of amount of water in the soil.
block - Factor five levels.
grain - Continuous - Grain yield per plant.
seeds - Count - Number of seeds per plant.
viablepeas - Binomial - Number of viable peas per plant.
totalpeas - Binomial - Total number of peas per plant.
data(soya)
a data.frame with 75 records and 7 variables.
Bonat, W. H. (2018). Multiple Response Variables Regression Models in R: The mcglm Package. Journal of Statistical Software, 84(4):1--30.
library(mcglm) library(Matrix) data(soya, package="mcglm") formu <- grain ~ block + factor(water) * factor(pot) Z0 <- mc_id(soya) fit <- mcglm(linear_pred = c(formu), matrix_pred = list(Z0), data = soya)#> Automatic initial values selected.anova(fit)#> Wald test for fixed effects #> Call: grain ~ block + factor(water) * factor(pot) #> <environment: 0x55608f71ee98> #> #> Covariate Chi.Square Df p.value #> 1 blockII 14.1367 4 0.0069 #> 2 factor(water)50 2.4555 2 0.2930 #> 3 factor(pot)30 63.9981 4 0.0000 #> 4 factor(water)50:factor(pot)30 30.3118 8 0.0002 #>