Hierarchical Probit Estimation for Dichotomized Data
bin2norm: A user-friendly interface to estimate normal distribution pa...
Get initial values from data
Minimal Gauss-Hermite Quadrature
GLMM (Multiple Thresholds per Study, Probit Link, Random Intercepts)
Bayesian MCMC (Multiple Thresholds per Study) using rstan
MLE with Numeric Integration (Multiple Thresholds per Study)
MLE (Single Threshold per Study)
GLM probit (Single Threshold per Study)
Weighted OLS (Initial value in Single Threshold per Study MLE)
Provides likelihood-based and hierarchical estimation methods for thresholded (binomial-probit) data. Supports fixed-mean and random-mean models with maximum likelihood estimation (MLE), generalized linear mixed model (GLMM), and Bayesian Markov chain Monte Carlo (MCMC) implementations. For methodological background, see Albert and Chib (1993) <doi:10.1080/01621459.1993.10476321> and McCulloch (1994) <doi:10.2307/2297959>.