See our website at http://jslefche.github.io/piecewiseSEM/
This version is a major update to the
piecewiseSEM package that usesa completely revised syntax that better reproduces the base R syntax and output. It is highly recommended that consult
vignette("piecewiseSEM") even if you have used the package before as it documents the many changes.
It also incorporates new functionality in the form of coefficient standardization and updated methods for R^2 for mixed models.
Currently supported model classes:
lm, glm, gls, pgls, sarlm, lme, glmmPQL, lmerMod, merModLmerTest, glmerMod
# Install development branch from github library(devtools) install_github("jslefche/piecewiseSEM@devel", build_vignette = TRUE) # Load library library(piecewiseSEM) # Read vignette vignette("piecewiseSEM") # Create fake data set.seed(1) data <- data.frame( x = runif(100), y1 = runif(100), y2 = rpois(100, 1), y3 = runif(100) ) # Store in SEM list modelList <- psem( lm(y1 ~ x, data), glm(y2 ~ x, "poisson", data), lm(y3 ~ y1 + y2, data), data ) # Run summary summary(modelList) # Address conflict using conserve = T summary(modelList, conserve = T) # Address conflict using direction = c() summary(modelList, direction = c("y2 <- y1")) # Address conflict using correlated errors modelList2 <- update(modelList, y2 %~~% y1) summary(modelList2)