| datacold {cold} | R Documentation |
Data
Description
This example is an artificial data.
Usage
data(datacold)
Format
A data frame with 390 observations on the following 4 variables.
Subjectidentifies de number of the individual profile. This vector contains observations of 30 individual profiles.
Treatmenta factor with levels
0and1.Timea numeric vector that identifies the number of the time points observed.
za numeric vector representing the response variable.
Examples
data(datacold)
mod0<- cold(z~Time*Treatment, data=datacold, time="Time",
id="Subject", dependence="ind")
summary (mod0)
modI<- cold(z~Time*Treatment, data=datacold, time="Time",
id="Subject", dependence="AR1")
summary (modI)
anova(mod0,modI)
plot(modI,which=1,factor=Treatment,xlab="Time (weeks)",
ylab="Count", main="Model AR1")
### independent with random intercept
mod0R <- cold(z ~ Time * Treatment, random = ~ 1, data = datacold,
time = "Time", id = "Subject", dependence = "indR")
summary(mod0R)
### independent with random intercept (dependence="indR")
### using cubature (integration = "cubature")
mod0R.C <- cold(z ~ Time * Treatment, random = ~ 1, data = datacold,
time = "Time", id = "Subject", dependence = "indR", integration = "cubature")
summary(mod0R.C)
randeff(mod0R.C)
### dependence="indR2"
## It takes a long time to run
## Using Monte Carlo method (integration = "MC")
mod0R2MC <- cold(z ~ Time * Treatment, ~ 1 + Time, datacold, time = "Time",
id = "Subject", dependence = "indR2", integration = "MC")
summary (mod0R2MC)
randeff(mod0R2MC)
## Using cubature (integration = "cubature")
mod0R2C<-cold(z ~ Time * Treatment, random = ~ 1 + Time, data = datacold,
time = "Time", id = "Subject", dependence = "indR2", integration = "cubature")
summary (mod0R2C)
[Package cold version 2.0-3 Index]