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, pbkrtest|
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
Jon Lefcheck <[email protected]>
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.
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