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psychonetrics

swMATH ID: 34796
Software Authors: Epskamp, Sacha
Description: Psychometric network models from time-series and panel data. Researchers in the field of network psychometrics often focus on the estimation of Gaussian graphical models (GGMs) – an undirected network model of partial correlations – between observed variables of cross-sectional data or single-subject time-series data. This assumes that all variables are measured without measurement error, which may be implausible. In addition, cross-sectional data cannot distinguish between within-subject and between-subject effects. This paper provides a general framework that extends GGM modeling with latent variables, including relationships over time. These relationships can be estimated from time-series data or panel data featuring at least three waves of measurement. The model takes the form of a graphical vector-autoregression model between latent variables and is termed the extit{ts-lvgvar} when estimated from time-series data and the extit{panel-lvgvar} when estimated from panel data. These methods have been implemented in the software package extit{psychonetrics}, which is exemplified in two empirical examples, one using time-series data and one using panel data, and evaluated in two large-scale simulation studies. The paper concludes with a discussion on ergodicity and generalizability. Although within-subject effects may in principle be separated from between-subject effects, the interpretation of these results rests on the intensity and the time interval of measurement and on the plausibility of the assumption of stationarity.
Homepage: https://cran.r-project.org/web/packages/psychonetrics/index.html
Source Code:  https://github.com/cran/psychonetrics
Dependencies: R
Keywords: network psychometrics; Gaussian graphical model; structural equation modeling; dynamics; time-series data; panel data
Related Software: qgraph; clusterGeneration; lvnet; metaSEM; lslx; R; gimme; graphicalVAR; GitHub; regsem; astsa; glasso; lavaan; LISREL; mgm; psych
Cited in: 3 Publications

Standard Articles

1 Publication describing the Software, including 1 Publication in zbMATH Year
Psychometric network models from time-series and panel data. Zbl 1447.62125
Epskamp, Sacha
2020

Cited in 1 Serial

3 Psychometrika

Cited in 1 Field

3 Statistics (62-XX)

Citations by Year