Piecewise Random-Effects Modeling Software Programs. Issue 1 (2nd January 2019) - Kohli, Nidhi; Peralta, Yadira; Bose, Maitreyee
Abstract : In this software review, we provide a brief overview of four different functions to fit a piecewise random-effects model with unknown changepoints (knots). Specifically, the four functions are: FitPMM from the R routine developed by (Zopluoglu, Harring, & Kohli, 2014), PROC NLMIXED from SAS, BayesPGM from the BayesianPGMM package in R developed by (Lock, Kohli, and Bose, 2018), and stancode_randomchangecorr function developed by (Brilleman, Howe, Wolfe, & Tilling, 2017) implemented to interface with Stan from R using the rstan package. We illustrate the estimation of the piecewise random-effects model using each of these functions by using a sample dataset. We provide appropriate commented code for the four functions, and briefly discuss the strengths and weaknesses of each function.