Standard Errors for EM Estimates in Variance Component Models

Friedl, H. und Kauermann, Göran (1999): Standard Errors for EM Estimates in Variance Component Models. Sonderforschungsbereich 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.

• Dokumententyp: Paper
• Keywords: EM algorithm, Gauss-Hermite Quadrature, Nonparametric Maximum Likelihood, Estimating Equation
• Fakultät: Mathematik, Informatik und Statistik > Statistik > Sonderforschungsbereich 386 ; Sonderforschungsbereiche > Sonderforschungsbereich 386
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• Sprache: Englisch