Subscribe Now Subscribe Today
Science Alert
Curve Top
Asian Journal of Mathematics & Statistics
  Year: 2010 | Volume: 3 | Issue: 2 | Page No.: 111-118
DOI: 10.3923/ajms.2010.111.118
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

Multilevel Linear Models Analysis using Generalized Maximum Entropy

A.D. Al-Nasser, O.M. Eidous and L.M. Mohaidat

The aimed of this study was to introduce the general multilevel models and discusses the Generalized Maximum Entropy (GME) estimation method that may be used to fit such models. The proposed procedure is applied to the two-level data model. The GME estimates were compared with Goldstein’s generalized least squares estimates. The comparisons are made by two criteria; the bias and the efficiency. We find that the estimates of two level’s model were substantially and significantly biased using Goldstein’s generalized least squares approach. However, the GME estimates are unbiased and consistent, we conclude that the GME approach is a recommended procedure to fit multilevel models. An application to a real data in education is also discussed.
PDF Fulltext XML References Citation Report Citation
  •    Generalized Parametric R-norm Information Measure
  •    A Noiseless Coding Theorem Connected with Generalized Renyi’s Entropy of Order α for Incomplete Power Probability Distribution pβ
  •    A Coding Theorem for the Information Measure of Order α and of Type β
How to cite this article:

A.D. Al-Nasser, O.M. Eidous and L.M. Mohaidat, 2010. Multilevel Linear Models Analysis using Generalized Maximum Entropy. Asian Journal of Mathematics & Statistics, 3: 111-118.

DOI: 10.3923/ajms.2010.111.118






Curve Bottom