Description

Fitting and evaluation of piecewise structural equation models, complete with goodness-of-fit tests, estimates of (standardized) path coefficients, and evaluation of individual model fits (e.g., through R-squared values). Compared with traditional variance-covariance based SEM, piecewise SEM allows for fitting of models to different distributions through GLM and/or hierarchical/nested random structures through (G)LMER. Supported model classes include: lm, glm, gls, pgls, sarlm, lme, glmmPQL, lmerMod, merModLmerTest, glmerMod.

Details

The primary functions in the package are psem which unites structural equations in a single model. summary.psem can be used on an object of class psem to provide various summary statistics for evaluation and interpretation.

Author(s)

Jon Lefcheck <lefcheckj@si.edu>

References

Shipley, Bill. "A new inferential test for path models based on directed acyclic graphs." Structural Equation Modeling 7.2 (2000): 206-218.

Shipley, Bill. Cause and correlation in biology: a user's guide to path analysis, structural equations and causal inference. Cambridge University Press, 2002.

Shipley, Bill. "Confirmatory path analysis in a generalized multilevel context." Ecology 90.2 (2009): 363-368.

Shipley, Bill. "The AIC model selection method applied to path analytic models compared using a d-separation test." Ecology 94.3 (2013): 560-564.

Grace, J.B., Johnson, D.A., Lefcheck, J.S., and Byrnes, J.E. "Standardized Coefficients in Regression and Structural Models with Binary Outcomes." Ecosphere 9(6): e02283.

Nakagawa, Shinichi, Paul CD Johnson, and Holger Schielzeth. "The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded." Journal of the Royal Society Interface 14.134 (2017): 20170213.