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Version 2.3.0

Last updated: 03 March 2023

To install

Run the following code to install the latest version from CRAN:

install.packages("piecewiseSEM")

Run the following code to install the development version:

devtools::install_github("jslefche/piecewiseSEM@devel")

Note: the development version may be unstable and lead to unanticipated bugs. Contact the package developer with any bugs or issues.

Getting Help

See our website at piecewiseSEM

There is an online resource available for SEM, including piecewiseSEM and lavaan, available https://jslefche.github.io/sem_book/

Version 2 is a major update to the piecewiseSEM package that uses a completely revised syntax that better reproduces the base R syntax and output. It is highly recommended that consult the resource above even if you have used the package before as it documents the many changes.

Currently supported model classes: lm, glm, gls, Sarlm, lme, glmmPQL, lmerMod, merModLmerTest, glmerMod. glmmTMB, gam

Example

# Load library
library(piecewiseSEM)

# Create fake data
set.seed(1)

data <- data.frame(
  x = runif(100),
  y1 = runif(100),
  y2 = rpois(100, 1),
  y3 = runif(100)
)

# Create SEM using `psem`
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)