lmfa
packagelmfa
allows to explore within-person changes and between person differences in measurement models in (intensive) longitudinal data by means of three-step continuous-time latent Markov factor analysis (LMFA).
You can download the development version from GitHub as follow:
install.packages("devtools"); library(devtools)
devtools::install_github("leonievm/lmfa")
After successful installation, you can perform LMFA by means of the three-step estimation. The package consists of three main functions that are shown below. For details about the function arguments, see the function documentations, which can be opened with ?functionname
.
step1(data,
indicators,
n_state = NULL,
n_fact = NULL,
modelselection = FALSE,
n_state_range = NULL,
n_fact_range = NULL,
n_starts = 25,
n_initial_ite = 10,
n_m_step = 10,
em_tolerance = 1e-8,
m_step_tolerance = 1e-3,
max_iterations = 1000,
n_mclust = 5)
step2(data, model)
step3(data,
identifier,
n_state,
postprobs,
timeintervals = NULL,
initialCovariates = NULL,
transitionCovariates = NULL,
n_starts = 25,
n_initial_ite = 10,
method = "BFGS",
max_iterations = 10000,
tolerance = 1e-10,
scaling = "proxi")
If you have any suggestions or if you found any bugs, please feel free to contact me via email.
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