psychonetrics (version 0.17.8)

psychonetrics-class: Class "psychonetrics"

Description

Main class for psychonetrics results.

Objects from the Class

Objects can be created by calls of the form new("psychonetrics", ...).

Slots

model:

Object of class "character": the model framework (e.g. "varcov", "lvm", "var1").

submodel:

Object of class "character": the submodel/type within the framework (e.g. "ggm").

parameters:

Object of class "data.frame": the parameter table (one row per model parameter, with estimates, standard errors, matrix/row/col indices and parameter numbers).

matrices:

Object of class "data.frame": bookkeeping table of the model matrices and their dimensions.

meanstructure:

Object of class "logical": whether a mean structure is included in the model.

computed:

Object of class "logical": whether the model has been estimated (run).

sample:

Object of class "psychonetrics_samplestats": the sample statistics used in estimation.

modelmatrices:

Object of class "list": the model-implied matrices in list form (per group).

log:

Object of class "psychonetrics_log": the logbook of actions performed on the model.

optim:

Object of class "list": the raw output of the optimizer.

fitmeasures:

Object of class "list": computed fit measures.

baseline_saturated:

Object of class "list": the baseline and saturated models used for fit computation.

equal:

Object of class "character": names of matrices constrained equal across groups (legacy representation; the parameters table is authoritative).

objective:

Object of class "numeric": the value of the fit function at the solution.

information:

Object of class "matrix": the Fisher information matrix.

identification:

Object of class "character": the identification method used (e.g. "loadings" or "variance").

optimizer:

Object of class "character": the optimizer used.

optim.args:

Object of class "list": arguments passed to the optimizer.

estimator:

Object of class "character": the estimator used (e.g. "ML", "FIML").

distribution:

Object of class "character": the assumed distribution (e.g. "Gaussian").

extramatrices:

Object of class "list": additional helper matrices used internally.

rawts:

Object of class "logical": whether raw time-series data are used.

Drawts:

Object of class "list": duplication/derivative matrices for raw time-series estimation.

types:

Object of class "list": the type of each model matrix per group.

cpp:

Object of class "logical": whether the C++ backend is used.

verbose:

Object of class "logical": whether progress messages are printed.

penalty:

Object of class "list": the penalty configuration for penalized (PML/PFIML) estimation, holding the penalty strength (lambda) and elastic-net mixing parameter (alpha).

Methods

resid

signature(object = "psychonetrics"): ...

residuals

signature(object = "psychonetrics"): ...

show

signature(object = "psychonetrics"): ...

summary

signature(object = "psychonetrics"): The print output extended with the main fit measures (log-likelihood, number of parameters, AIC, BIC, RMSEA, CFI, TLI). Use fit for the complete list of fit measures.

Author

Sacha Epskamp

Examples

showClass("psychonetrics")