Estimates latent Gaussian joint distributions for normal continuous, binary, and ordinal variables using marginal summaries from independent studies of a common population. Fits a pairwise Gaussian working criterion using exact summary moments, with study-level sandwich uncertainty. Supports prespecified independent groups, joint event probabilities, and synthetic patient generation. Identification requires repeated joint reporting of variable pairs; heterogeneous populations, rare categories, and small study collections require caution.
Joint distribution estimation from marginal study summaries, by Xuekui Zhang (University of Victoria; ORCID 0000-0003-4728-2343).
Install from a built source tarball with R CMD INSTALL summary2joint_0.1.0.tar.gz.
Then use library(summary2joint) and see ?fit_summary_copula or
vignette("summary2joint").
The package compiles the unchanged manuscript C++ kernel at installation. There is no runtime compiler, source-file dependency, or persistent compilation cache. Exports cover unrestricted/grouped fits, joint probabilities, and synthetic patient generation. Numerical defaults are unchanged. The original manuscript source files and saved results are retained outside this package.
License: GPL-3. Local development version; not submitted to CRAN.