umx

umx is a structural equation modelling package designed to make SEM easier to build, modify, and report.

It includes high-level functions for complex models such as multi-group twin models, as well as for graphical model output.

Grab it from CRAN with

install.packages("umx")
library(umx)
?umx

The best way to learn what is on offer is to use the help ('?umx' works) and the online tutorial: tbates.github.io

umx stands for "user" OpenMx functions. umx contains over 100 functions which build on OpenMx, and are designed to automate activities such as labelling, setting start values etc., and also provides umxRAM and umxPath functions that make Structural Equation Modeling in R straightforward.

Some highlights include:

1. Building Path Models
   • umxRAM() # mxModel with an R-like data = parameter, no need to specify type = "RAM", + auto-discovery of manifests and latents from the paths you write
   • umxPath() # mxPath on steroids: one-word settings to set var , mean cov, fixedAt and more. Great time-saver!
2. Reporting output
   • umxSummary(model) # Get a brief summary of model fit, similar to a journal report (Χ², p, CFI, TLI, & RMSEA). Optionally show the path loadings
   • plot(model, std=T, digits = 3, file = "name") # Create a graphical representation of model!
   • umx_time(model) # Report the time taken by a model in a compact programable format
3. Modify models
   • umxModify() *# Modify and run a model. You can add objects, drop or add paths, including by regular-expression label matching), re-name the model, re-run, and even return the comparison. All in 1 line *
   • umxGetParameters(model, regex = "as_r_2c_[0-9]", free = T) # A powerful assistant to get labels from a model. like omxGetParameters but uses regular expressions.
4. Twin models
   • umxACE() # 1-line function handling twin ACE modeling with aplomb paths are labeled, and works with plot() and umxSummary
   • umxIP(), umxGxE(), umxCP()…
5. Lower level helpers, data helpers, etc.
   • umxStart() # Add plausible start values to RAM or matrix models, or matrices: very helpful
   • umxLabel() # Add systematic labels to paths ("var1_to_var2") and matrix cells ("a_r1c1"). This is great for setting, equating and dropping paths by label!
   • umxHcor(data, use = "pairwise.complete.obs") # Compute appropriate pair-wise correlations for mixed data types.
6. Helpers for easy-to-forget option names
   • umx_set_cores()
   • umx_set_optimizer()

Dozens more (?umx to see them all). Check out the "family links" in any help file also!

Feel free to use, and improve: Log suggestions using the Github comments. Tell your friends! Get awesome publications :-)

You can install the development version from github:

install.packages("devtools")
library("devtools")
install_github("tbates/umx")
library("umx")
?umx