Documentation

umx

Build Status Github commits cran version Monthly Downloads Total Downloads Rdoc DOI License

Road map, and Tutorials (let me know what you'd like, or perhaps a book?)

umx is a structural equation modeling package designed to make SEM easier, from building, to modifying and reporting. Please cite as: citation("umx"):

Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R. Twin Research and Human Genetics, 22, 27-41. DOI:10.1017/thg.2019.2

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

Install it from CRAN:

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

Most functions have extensive and practical examples (even figures for the twin models): so USE THE HELP :-).

See what is on offer with '?umx'. There are online tutorials at tbates.github.io.

umx stands for "user" OpenMx functions. It provides over 100 functions, but most importantly the high-level umxRAM functions that makes path-based SEM in R straightforward from model specification to plot, along with a suite of high-level twin modelling functions. These are supported by dozens of low-level functions automating activities such as labeling, setting start values etc., and helping with data-wrangling, plotting etc.

Some highlights include:

  1. Building Path Models
    • umxRAM() # mxModel with smart data = parameter, automatic labels, start, run, plot, and auto-discovery of manifests and latents from the paths you write
    • umxPath() # write paths but with one-word settings to set var , mean cov, fixedAt 'v.m.' = and more.
  2. Reporting output
    • umxSummary(model) # A fit summary designed for journal reporting (Χ², p, CFI, TLI, & RMSEA). Optionally show the path loadings
    • plot(model, std=T, digits = 3, file = "name") # Graphical, model in your browser! or edit in programs like OmniGraffle
  3. Modify models
    • umxModify() *# Modify and run a model. You can add objects, drop or add paths, including by wildcard label matching), re-name the model, re-run, and even return the comparison. All in 1 line *
    • parameters(m1, "below", .1, pattern="_to_")) # A powerful assistant to get labels and values from a model (e.g. all 'to' params, below .1 in value)
  4. Twin modeling!
    • umxACE # Twin ACE modeling with aplomb paths are labeled! Works with plot() and umxSummary!
    • umxCP, umxIP, umxGxE, umxCP, umxGxEbiv, umxSexLim
    • umxACE
  5. Easy-to-remember options
    • umx_set_cores()
    • umx_set_optimizer()
  6. Many more miscellaneous helpers e.g.
    • umx_time(model1, model2) reports and compares run times in a compact programmable format (also "start" and "stop" a timer)
    • umxHetcor(data, use = "pairwise.complete.obs") # Compute appropriate pair-wise correlations for mixed data types.
    • Dozens more: Check out the "family links" in ?umx and in any help file!

Feel free to use, and submit code and requests via Github. Tell your friends! Publish more good science :-)

For thrill-seekers and collaborators only: the bleeding-edge development version is here:

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