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Dynamic structural equation models

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Package dsem fits dynamic structural equation models, which includes as nested submodels:

  1. structural equation models
  2. vector autoregressive models
  3. dynamic factor analysis
  4. state-space autoregressive integrated moving average (ARIMA) models

The model has several advantages:

  • It estimates direct, indirect, and total effects among system variables, including simultaneous and lagged effects and recursive (cyclic) dependencies
  • It can estimate the cumulative outcome from press or pulse experiments or initial conditions that differ from the stationary distribution of system dynamics
  • It estimates structural linkages as regression slopes while jointly imputing missing values and/or measurement errors
  • It is rapidly fitted as a Gaussian Markov random field (GMRF) in a Generalized Linear Mixed Model (GLMM), with speed and asymptotics associated with each
  • It allows granular control over the number of parameters (and restrictions on parameters) used to structure the covariance among variables and over time,

dsem is specifically intended as a minimal implementation, and uses standard packages to simplify input/output formatting:

  • Input: time-series defined using class ts, with NA for missing values
  • Input: structural trade-offs specified using syntax defined by package sem
  • Output: visualizing estimated trade-offs using igraph
  • Output: access model output using standard S3-generic functions including summary, predict, residuals, simulate, and AIC

Please see package vignettes for more details regarding syntax and features.

Citation

For description of dynamic structural equation models and path-lag interface

Thorson, J. T., Andrews, A. G., Essington, T., & Large, S. (2024). Dynamic structural equation models synthesize ecosystem dynamics constrained by ecological mechanisms. Methods in Ecology and Evolution 15(4): 744-755. https://doi.org/10.1111/2041-210X.14289

For description of generalized graphical mixed models in general

Thorson, J. T. (2026). Generalized graphical mixed models connect ecological theory with widely used statistical models. Methods in Ecology and Evolution, 17(4), 1290–1302. https://doi.org/10.1111/2041-210x.70272

For description of moderated DSEM and varying path coefficients

Thorson, J. T., & Kristensen, K. (In press). Ecological examples of nonstationarity, nonlinearity, and statistical interactions in dynamic structural equation models. Methods in Ecology and Evolution. https://ecoevorxiv.org/repository/view/11418/

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