Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences) - Softcover

Eliason, Scott R.

Softcover

ISBN 10: 0803941072 ISBN 13: 9780803941076

Publisher: SAGE Publications, Inc, 1993

Synopsis

"Maximum Likelihood Estimation. . . provides a useful introduction. . . it is clear and easy to follow with applications and graphs. . . . I consider this a very useful book. . . . well-written, with a wealth of explanation. . ."

--Dougal Hutchison in Educational Research

Eliason reveals to the reader the underlying logic and practice of maximum likelihood (ML) estimation by providing a general modeling framework that utilizes the tools of ML methods. This framework offers readers a flexible modeling strategy since it accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models that link a system of endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, Eliason discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.

About this title

About the Author

RESEARCH AND TEACHING INTERESTS
Quantitative Methodology and Statistics; Sociology of Work, Occupations, and Labor Markets;
Economic Sociology; Stratification; Life Course

Edition details

• Publisher: SAGE Publications, Inc
• Publication date: 1993
• Language: English
• ISBN 10: 0803941072
• ISBN 13: 9780803941076
• Binding: Paperback
• Edition number: 1
• Number of pages: 96