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fastsemR is an R interface to fastsem, a compiled Nim SEM engine that supports:
- ML (full-data maximum likelihood) with analytical gradient and optional GPU acceleration
- FIML (full-information ML for missing data and definition variables)
- DWLS / WLSMV (diagonally weighted least squares for ordinal indicators)
- Multi-group models with configural or constrained parameters
- Equality constraints, parameter bounds, and derived parameters (delta-method SEs)
- Cluster-robust standard errors
- Standardised estimates (StdAll) with SEs via the delta method
The package translates umx / OpenMx RAM model objects into fastsem lavaan syntax, fits the model, and injects estimates back into the model object so that summary(), omxGetParameters(), and umxCompare() continue to work.
Installation
# Install from GitHub (requires devtools)
devtools::install_github("lf-araujo/fastsemR")The compiled shared library is downloaded automatically from GitHub Releases the first time the package is loaded. To force a re-download (e.g. after a fastsem update):
If you have built the library yourself from the fastsem source tree (nimble buildRnim), point the package to your local build:
fastsem_load("~/fastsem/libfastsem_r.so")Example 1 — General statistics: mediation analysis
Decompose the effect of engine displacement (disp) on fuel economy (mpg) through vehicle weight (wt), labelling paths a, b, and c_prime so that the indirect effect ab := a * b is computed via the delta method.
library(fastsemR)
library(umx)
df <- as.data.frame(scale(mtcars[, c("mpg", "disp", "wt")]))
m <- umxRAM("Mediation",
umxPath("disp", to = "wt", labels = "a"),
umxPath("wt", to = "mpg", labels = "b"),
umxPath("disp", to = "mpg", labels = "c_prime"),
umxPath(var = c("disp", "wt", "mpg")),
umxPath(means = c("disp", "wt", "mpg")),
data = df, autoRun = FALSE
)
m_fit <- run_fastsem(m)
summary(m_fit)fastsem -- FIML [SE: OIM]
N=32 free params=9 df=0
# Parameter Estimate SE z
─────────────────────────────────────────────────────────────
1 a (disp->wt) 0.888 0.038 23.36
2 b (wt->mpg) -0.541 0.112 -4.83
3 c_prime (disp->mpg) -0.408 0.112 -3.64
...The indirect effect and its SE are computed automatically when a derived_params line is added to the syntax, e.g.:
# Append to the umxPath-generated syntax before fitting
syntax <- paste(umx_to_lavaan(m), "ab := a * b", sep = "\n")
res <- fastsem_fit(syntax, df)
cat("Indirect effect:", res$estimates[res$paramNames == "ab"],
" SE:", res$se[res$paramNames == "ab"], "\n")Contributing
Contributions are welcome. Please open an issue at https://github.com/lf-araujo/fastsemR/issues for bug reports, feature requests, or questions about the R interface. For issues specific to the underlying Nim engine (numerical results, GPU kernels, performance), file at https://github.com/lf-araujo/fastsem/issues.
Pull requests targeting main should pass R CMD check with no errors or warnings; the GitHub Actions workflow runs the same checks on Linux, macOS, and Windows.
License
fastsemR is released under the MIT License. See LICENSE for details. The compiled fastsem engine is distributed under its own license; see the fastsem repository for terms.