latrend (version 1.1.0)

lcMethodStratify: Specify a stratification method

Description

Specify a stratification method

Usage

lcMethodStratify(
  response,
  stratify,
  center = meanNA,
  nClusters = NaN,
  clusterNames = NULL,
  time = getOption("latrend.time"),
  id = getOption("latrend.id"),
  name = "stratify"
)

Arguments

response

The name of the response variable.

stratify

An expression returning a number or factor value per trajectory, representing the cluster assignment. Alternatively, a function can be provided that takes separate trajectory data.frame as input.

center

The function for computing the longitudinal cluster centers, used for representing the cluster trajectories.

nClusters

The number of clusters. This is optional, as this can be derived from the largest assignment number by default, or the number of factor levels.

clusterNames

The names of the clusters. If a factor assignment is returned, the levels are used as the cluster names.

time

The name of the time variable.

id

The name of the trajectory identification variable.

name

The name of the method.

See Also

Other lcMethod implementations: lcMethod-class, lcMethodAkmedoids, lcMethodCrimCV, lcMethodCustom, lcMethodDtwclust, lcMethodFeature, lcMethodFunFEM, lcMethodGCKM, lcMethodKML, lcMethodLMKM, lcMethodLcmmGBTM, lcMethodLcmmGMM, lcMethodLongclust, lcMethodMclustLLPA, lcMethodMixAK_GLMM, lcMethodMixtoolsGMM, lcMethodMixtoolsNPRM, lcMethodRandom

Examples

# NOT RUN {
data(latrendData)
# Stratification based on the mean response level
method <- lcMethodStratify("Y", mean(Y) > 0,
   clusterNames = c("Low", "High"), id = "Id", time = "Time")
model <- latrend(method, latrendData)
summary(model)

# Stratification function
stratfun <- function(trajdata) {
   trajmean <- mean(trajdata$Y)
   factor(trajmean > 1.7,
      levels = c(FALSE, TRUE),
      labels = c("Low", "High"))
}
method <- lcMethodStratify("Y", stratfun, id = "Id", time = "Time")

# Multiple clusters
stratfun3 <- function(trajdata) {
   trajmean <- mean(trajdata$Y)
   cut(trajmean,
      c(-Inf, .5, 2, Inf),
      labels = c("Low", "Medium", "High"))
}
method <- lcMethodStratify("Y", stratfun3, id = "Id", time = "Time")
# }