Longitudinal data with dropouts: a comparison of pattern mixture models with complete case analysis

Storck, S.; Kastner, C. and Toutenburg, Helge (2000): Longitudinal data with dropouts: a comparison of pattern mixture models with complete case analysis. Collaborative Research Center 386, Discussion Paper 188

Abstract

Pattern mixture models constitute an alternative to selection models (Little & Rubin, 1987). Little & Wang (1996) introduced pattern mixture models for analyzing multivariate normal longitudinal data with missing values. This paper was the theoretical foundation and the induce to investigate the small sample properties of pattern mixture models compared with complete case analysis. The main point of interest, of the simulations, was the mean square error of the estimated model parameters. Parameters estimated by the pattern mixture model are very satisfying under ignorable mechanism but they have to be scanned carefully under nonignorable mechanism.

• Item Type: Paper
• 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