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)