Piecewise Random-Effects Modeling Software Programs

Nidhi Kohli, Yadira Peralta, Maitreyee Bose

Research output: Contribution to journalReview article

4 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)156-164
Number of pages9
JournalStructural Equation Modeling
Volume26
Issue number1
DOIs
StatePublished - Jan 2 2019

Keywords

  • piecewise function
  • random changepoint
  • software

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