CrossGEE {CrossCarry} | R Documentation |
Provides a GEE model for the data of a crossover design with S sequences of T periods. There must be one observation of each experimental unit in each period.
CrossGEE(
response,
period,
treatment,
id,
carry,
covar = NULL,
data,
family = gaussian(),
correlation = "independence",
formula = NULL
)
response |
A character string specifying the name of the response variable of the crossover experimental design |
period |
A character string specifying the name of vector with the observation period of the responses of the crossover experimental design |
treatment |
A character string specifying the name of vector with the treatment applied at each observation of the crossover experimental design |
id |
A character string specifying the name of vector which identifies the experimental units. The length of ‘id’ should be the same as the number of observations. Data are assumed to be sorted so that observations on each cluster appear as contiguous rows in data. If data is not sorted this way, the function will not identify the clusters correctly. If data is not sorted this way, a warning will be issued. |
carry |
A vector of character string specifying the name set of dummy variables that indicates the treatment applied in the previous period of each experimental unit. They must be 0 in period 1 |
covar |
A vector of character string specifying the name of possible covariates of the crossover experimental design |
data |
A data frame with all the variables of the crossover experimental design |
family |
See corresponding documentation to |
correlation |
a character string specifying the correlation structure. The following are permitted: "independence", "exchangeable", "ar1" and "unstructured" |
formula |
A formula related the response variable with the explanatory
variables. If it is |
QIC
The QIC of the models: The model are fitted by geeglm
model
The model fitted by geeglm
.
data(Water)
model <- CrossGEE(response="LCC", covar=c("Age"), period="Period",
treatment = "Treatment", id="ID", carry="Carry_Agua",
family=gaussian(),correlation ="ar1" ,data=Water)
model$QIC
model$model
summary(model$model)