Marginal Posterior means of \(b_j\) plotted against the marginal posterior means of \(a_j\). Each point is labeled with the number of the corresponding Item.
For the Three-Parameter Normal Ogive Item Response Model (3pno), the size of the numbers refers to the marginal posterior means of \(c_j\).
The Potential Scale Reduction Factor (Rhat) is calculated for each chain, bairt generates a single MCMC and evaluates convergence by breaking the chain in three sub chains and comparing the between- and within-subchain variance.
The black color suggests convergence and red items indicate convergence problems (Rhat greater than 1.1).
check.plot(mcmclist, ...)A mcmc.2pnob or mcmc.3pnob class object.
Further arguments.
A plot of the discrimination marginal posterior means against difficulty marginal posterior means. For the Three-parameter model the guessing marginal posterior means are represented by the number size of the item.
If converg.test = TRUE the items with Rhat menor that 1.1 are print in red color. It is useful for quick check of the convergence.
Johnson, V. E. & Albert, J. H. (1999). Ordinal Data Modeling. New York: Springer.
Gelman, A., Carlin, J. B., Stern, H. S. & Rubin, B. (2004). Bayesian Data Analysis.New York: Chapman & Hall/CRC.