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A Fast Scoring Algorithm for Maximum Likelihood Estimation in Unbalanced Mixed Models With Nested Random Effects

Author(s):
Longford, Nicholas T.
Publication Year:
1987
Report Number:
RR-87-13
Source:
ETS Research Report
Document Type:
Report
Page Count:
30
Subject/Key Words:
Data Analysis, Fisher Scoring Algorithm, Maximum Likelihood Statistics, Statistical Analysis

Abstract

A fast Fisher scoring algorithm for maximum likelihood estimation in unbalanced mixed models with nested random effects is described. The algorithm uses explicit formulae for the inverse and the determinant of the covariance matrix, and avoids inversion of large matrices. Description of the algorithm concentrates on computational aspects for large sets of data. (SGK) (30pp.)

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