contrasts_DI {DImodels}  R Documentation 
This function calculates and tests contrasts using glht
for a model object created by the DI
or autoDI
functions.
contrasts_DI(object, contrast, contrast_vars, ...)
object 

contrast 
The coefficients to generate the contrast. There are three options to specify these coefficients: A list with each element being a vector of the same length as the number of linear coefficients in the model. The list can be named for tracking the contrasts. A matrix with the same number of columns as the number of linear coefficients in the model. The matrix can be given row names to track the different contrasts. A numeric vector with the length being a multiple of the number of coefficients in the matrix. Overrides 
contrast_vars 
A quicker and easier way to specify contrast coefficients for testing categorical variables. A nested named list with same names as the categorical variables in the model and same lengths as levels of those variables can be specified and the contrast will be calculated without the user having to specify the remaining variables. Will be overridden if Recommended for only testing cateogrical variables in the model. 
... 
Additional arguments passed to the 
The contrasts are calculated and tested using the glht
function in the multcomp
package.
An object of class glht
is returned
Rafael A. Moral, John Connolly, Rishabh Vishwakarma and Caroline Brophy
Kirwan L, J Connolly, JA Finn, C Brophy, A Lüscher, D Nyfeler and MT Sebastia (2009) Diversityinteraction modelling  estimating contributions of species identities and interactions to ecosystem function. Ecology, 90, 20322038.
Torsten Hothorn, Frank Bretz and Peter Westfall (2008). Simultaneous Inference in General Parametric Models. Biometrical Journal 50(3), 346–363.
## Load the Switzerland data
data(Switzerland)
## Summarise the Switzerland data
summary(Switzerland)
## Fit a DI model
m1 < DI(y = "yield", prop = 4:7, treat = 'nitrogen', DImodel = 'AV',
density = 'density', estimate_theta = FALSE, data = Switzerland)
summary(m1)
## Contrasts for difference between monocultures of p1 and p2, p3 and p4, p2 and p3
con1 < contrasts_DI(object = m1,
contrast = list('p1vp2 Mono' = c(1, 1, 0, 0, 0, 0, 0),
'p3vp4 Mono' = c(0, 0, 1, 1, 0, 0, 0),
'p2vp3 Mono' = c(0, 1, 1, 0, 0, 0, 0)))
summary(con1)
## Contrasts for 50:50 mixture of p1 and p2 vs 50:50 mixture of p3 and p4
con2 < contrasts_DI(object = m1,
contrast = list('p1p2 vs p3p4' = c(0.5, 0.5, 0.5, 0.5, 0, 0, 0)))
summary(con2)
## Example using contrast_vars
data(sim2)
### Fit model with block
m2 < DI(y = "response", prop = 3:6, DImodel = 'FULL', block = 'block',
estimate_theta = FALSE, data = sim2)
summary(m2)
### contrast for average of first two blocks vs third block
con3 < contrasts_DI(object = m2,
contrast_vars = list('block' = list('1_2vs3' = c(0.5, 0.5, 1, 0))))
summary(con3)