TY - JOUR
T1 - Piecewise Random-Effects Modeling Software Programs
AU - Kohli, Nidhi
AU - Peralta, Yadira
AU - Bose, Maitreyee
PY - 2019/1/2
Y1 - 2019/1/2
N2 - 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.
AB - 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.
KW - piecewise function
KW - random changepoint
KW - software
UR - https://www.scopus.com/pages/publications/85060554422
UR - https://www.scopus.com/pages/publications/85060554422#tab=citedBy
U2 - 10.1080/10705511.2018.1516507
DO - 10.1080/10705511.2018.1516507
M3 - Review article
AN - SCOPUS:85060554422
SN - 1070-5511
VL - 26
SP - 156
EP - 164
JO - Structural Equation Modeling
JF - Structural Equation Modeling
IS - 1
ER -