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
lm, glm, gls, pgls, sarlm, lme, glmmPQL, lmerMod,
|Depends:||R (>= 3.5.0), nlme,|
functions in the package are
psem which unites structural
equations in a single model.
summary.psem can be used on an object of
psem to provide various summary statistics for evaluation and
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.