论文信息 - Efficient computational procedures for the estimation of parameters in multilevel models based on iterative generalised least squares

Efficient computational procedures for the estimation of parameters in multilevel models based on iterative generalised least squares

Abstract Computational procedures are described for the efficient estimation of the fixed and random parameters in multilevel random coefficient linear models. The estimation procedure is based on iterative generalised least squares. A number of special cases are described and the procedure is implemented within a general purpose statistical package.

Harvey Goldstein | Jon Rasbash | H. Goldstein | J. Rasbash

[1] N. Longford. A fast scoring algorithm for maximum likelihood estimation in unbalanced mixed models with nested random effects , 1987 .

[2] S. R. Searle,et al. On Deriving the Inverse of a Sum of Matrices , 1981 .

[3] S. R. Searle,et al. Matrix Algebra Useful for Statistics , 1982 .

[4] H. Goldstein. Multilevel mixed linear model analysis using iterative generalized least squares , 1986 .

[5] H. Goldstein. Restricted unbiased iterative generalized least-squares estimation , 1989 .

[6] H. Goldstein,et al. Multilevel Models in Educational and Social Research. , 1989 .

[7] Anthony S. Bryk,et al. A Hierarchical Model for Studying School Effects , 1986 .

[8] Bob Prosser,et al. ML3: Software for Three-Level Analysis , 1991 .