Efficient Gibbs sampling procedures for multivariate random effect probit model estimation.
The mvreprobit R package contains code associated with the article
Steele, F., Zhang, S., Grundy, E., and Burchardt, T. (2022). Longitudinal analysis of exchanges of support between parents and children in the UK.
It contains tailored Gibbs sampling procedures for multivariate random effect probit modelling. It currently includes the following models fitted in the paper: a 2-level model (1 random effect) and a 3-level model. The latter is an extension of the standard 3-level hierarchical model to include a time-varying level 3 random effect, giving 3 random effects in total. The code is concise, self-explanatory, and can be extended to any number of response variables and random effects of arbitrary multilevel designs.
See Wiki page
1. Four-process 2-level (1 random effect) probit model
2. Four-process 3-level (3 random effects) probit model
- truncnorm
- mvtnorm
- MCMCpack
- matrixcalc
GPL v3.0