Small-area estimation with missing data using a multivariate linear random effects model

Ngaruye, I.; von, Rosen, D.; Singull, M.

doi:10.1007/s42081-018-0015-5

Abstract

In this article, small-area estimation with multivariate data that follow a monotonic missing sample pattern is addressed. Random effects growth curve models with covariates are formulated. A likelihood-based approach is proposed for estimation of the unknown parameters. Moreover, the prediction of random effects and predicted small-area means are also discussed.

Keywords

Monotone sample; Multivariate linear model; Repeated measures data

Published in

Japanese Journal of Statistics and Data Science
2018, volume: 1, number: 1, pages: 23-37
Publisher: Springer Science and Business Media B.V.

SLU Authors

von Rosen, Dietrich
- Department of Energy and Technology, Swedish University of Agricultural Sciences
- Linköping University

UKÄ Subject classification

Probability Theory and Statistics

Publication identifier

DOI: https://doi.org/10.1007/s42081-018-0015-5

Permanent link to this page (URI)

https://res.slu.se/id/publ/142871