Standard Errors for EM Estimates in Variance Component Models

Friedl, H. and Kauermann, Göran (1999): Standard Errors for EM Estimates in Variance Component Models. Collaborative Research Center 386, Discussion Paper 145

Abstract

A procedure is derived for computing standard errors in random intercept models for estimates obtained from the EM algorithm. We discuss two different approaches: a Gauss-Hermite quadrature for Gaussian random effect models and a nonparametric maximum likelihood estimation for an unspecified random effect distribution. An approximation of the expected Fisher information matrix is proposed which is based on an expansion of the EM estimating equation. This allows for inferential arguments based on EM estimates, as demonstrated by an example and simulations.

• Item Type: Paper
• Keywords: EM algorithm, Gauss-Hermite Quadrature, Nonparametric Maximum Likelihood, Estimating Equation
• Faculties: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics
• Language: English