Description Details upmfit functions

The upmfit package uses methods described by McIntosh, et al. "Extensions to Bayesian Generalized Linear Mixed Effects Models for Household Tuberculosis Transmission," *Statistics in Medicine* (2017), to implement functions that generate model script in the JAGS language for the Unified Probability Model (UPM), and to run a JAGS MCMC sampler for posterior probability desnity estimation with the model script.

It should be noted that, while the UPM and R package upmfit were designed specifically with tuberculosis household contact studies in mind, the method is applicable to any scenario where there are two competing risks for a single outcome with unobserved linkage between the sources of risk and the outcome. Example situation where this method could be applicable are in profiling the risk of MRSA infection from a nosocomial versus other source, or in modeling risk of TB infection among populations utilizing homeless shelters. Non-clinical examples could be in an industrial process control setting where a manufactured item has two sources of degradation, one observed and one unobserved, or in a chemical mixing procedure where catalysis can occur from the mixing of an exogenous agent or autocatalysis.

upmfit has: function *upmbuilder()* to create the JAGS model script and display a (possibly redefined) design matrix from a design matrix input by the user; *upmrun()* to generate posterior parameter estimates via a Markov Chain Monte Carlo sampler; and synthetic dataset *upmdata*.

For a longer introduction, see the introductory vignette for this package. Use command vignette("upm-primer", package="upmfit") or browseVignettes(package = "upmfit") to access the vignettes.

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