lcMethodLcmmGMM: Specify GMM method using lcmm

In latrend: A Framework for Clustering Longitudinal Data

Specify GMM method using lcmm

Description

Growth mixture modeling through latent-class linear mixed modeling.

Usage

lcMethodLcmmGMM(
  fixed,
  mixture = ~1,
  random = ~1,
  classmb = ~1,
  time = getOption("latrend.time"),
  id = getOption("latrend.id"),
  init = "lme",
  nClusters = 2,
  ...
)

Arguments

fixed	The fixed effects formula.
mixture	The mixture-specific effects formula. See lcmm::hlme for details.
random	The random effects formula. See lcmm::hlme for details.
classmb	The cluster membership formula for the multinomial logistic model. See lcmm::hlme for details.
time	The name of the time variable.
id	The name of the trajectory identifier variable. This replaces the subject argument of lcmm::hlme.
init	Alternative for the B argument of lcmm::hlme, for initializing the hlme fitting procedure. This is only applicable for nClusters > 1. Options: "lme.random" (default): random initialization through a standard linear mixed model. Assigns a fitted standard linear mixed model enclosed in a call to random() to the B argument. "lme", fits a standard linear mixed model and passes this to the B argument. "gridsearch", a gridsearch is used with initialization from "lme.random", following the approach used by lcmm::gridsearch. To use this initalization, specify arguments gridsearch.maxiter (max number of iterations during search), gridsearch.rep (number of fits during search), and gridsearch.parallel (whether to enable parallel computation). NULL or "default", the default lcmm::hlme input for B is used. The argument is ignored if the B argument is specified, or nClusters = 1.
nClusters	The number of clusters to fit. This replaces the ng argument of lcmm::hlme.
...	Arguments passed to lcmm::hlme. The following arguments are ignored: data, fixed, random, mixture, subject, classmb, returndata, ng, verbose, subset.

References

\insertRef

proustlima2017estimationlatrend

\insertRef

proustlima2019lcmmlatrend

See Also

Other lcMethod implementations: getArgumentDefaults(), getArgumentExclusions(), lcMethod-class, lcMethodAkmedoids, lcMethodCrimCV, lcMethodDtwclust, lcMethodFeature, lcMethodFunFEM, lcMethodFunction, lcMethodGCKM, lcMethodKML, lcMethodLMKM, lcMethodLcmmGBTM, lcMethodMclustLLPA, lcMethodMixAK_GLMM, lcMethodMixtoolsGMM, lcMethodMixtoolsNPRM, lcMethodRandom, lcMethodStratify

Examples

data(latrendData)

if (rlang::is_installed("lcmm")) {
  method <- lcMethodLcmmGMM(
    fixed = Y ~ Time,
    mixture = ~ Time,
    random = ~ 1,
    id = "Id",
    time = "Time",
    nClusters = 2
  )
  gmm <- latrend(method, data = latrendData)
  summary(gmm)

  # define method with gridsearch
  method <- lcMethodLcmmGMM(
    fixed = Y ~ Time,
    mixture = ~ Time,
    random = ~ 1,
    id = "Id",
    time = "Time",
    nClusters = 3,
    init = "gridsearch",
    gridsearch.maxiter = 10,
    gridsearch.rep = 50,
    gridsearch.parallel = TRUE
  )
}

latrend documentation built on March 31, 2023, 5:45 p.m.