esa: Ergodic Subspace Analysis

In psychonetrics: Structural Equation Modeling and Confirmatory Network Analysis

Description

These functions implement Ergodic Subspace Analysis by von Oertzen, Schmiedek \& 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., & Voelkle, M. C. (2020). Ergodic Subspace Analysis. Journal of Intelligence, 8(1), 3.

psychonetrics documentation built on Oct. 26, 2021, 1:06 a.m.