esa: Ergodic Subspace Analysis

In psychonetrics: Structural Equation Modeling and Confirmatory Network Analysis

Ergodic Subspace Analysis

Description

These functions implement Ergodic Subspace Analysis by von Oertzen, Schmiedek and Voelkle (2020). The functions can be used on the output of a dlvm1 model, or manually by supplying a within persons and between persons variance-covariance matrix.

Usage

esa(x, cutoff = 0.1,
    between = c("crosssection", "between"))
esa_manual(sigma_wp, sigma_bp, cutoff = 0.1)
## S3 method for class 'esa'
print(x, printref = TRUE, ...)
## S3 method for class 'esa_manual'
print(x, printref = TRUE, ...)
## S3 method for class 'esa'
plot(x, plot = c("observed", "latent"), ...)
## S3 method for class 'esa_manual'
plot(x,  ...)

Arguments

x	Output of a dlvm1 model
sigma_wp	Manual within-person variance-covariance matrix
sigma_bp	Manual between-person variance-covariance matrix
cutoff	Cutoff used to determine ergodicity
printref	Logical, should the reference be printed?
plot	Should ergodicity of observed or latent variables be plotted?
between	Should the between-persons variance-covariance matrix be based on exected cross-sectional or between-person relations
...	Not used

Value

For each group a esa_manual object with the following elements:

ergodicity	Ergodicity values of each component
Q_esa	Component loadings
V_bp	Between persons subspace
V_ergodic	Ergodic subspace
V_wp	Within person subspace
cutoff	Cutoff value used

Author(s)

Sacha Epskamp <[e-mail]>

References

von Oertzen, T., Schmiedek, F., and Voelkle, M. C. (2020). Ergodic Subspace Analysis. Journal of Intelligence, 8(1), 3.

psychonetrics documentation built on June 22, 2024, 10:29 a.m.