Asymptotic Corrections for Multivariate Posterior Moments with Factored Likelihood Functions

Abstract

Asymptotic corrections are used to compute the means and the variance-covariance matrix of multivariate posterior distributions that are formed from a normal prior distribution and a likelihood function that factors into separate functions for each variable in the posterior distribution. The approximations are illustrated using data from the National Assessment of Educational Progress (NAEP). These corrections produce much more accurate approximations than those produced by two different normal approximations. In a second potential application, the computational methods are applied to logistic regression models for severity adjustment of hospital-specific mortality rates.

Key Words:

• EM algorithm
• Item response model
• Laplace expansion