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Maximum Likelihood Estimation for Sample Surveys

Publisher: 
Chapman & Hall/CRC
Number of Pages: 
375
Price: 
79.95
ISBN: 
9781584886327
Date Received: 
Monday, May 28, 2012
Reviewable: 
No
Include In BLL Rating: 
No
Reviewer Email Address: 
R. L. Chambers, D. G. Steel, Suojin Wang, and A. H. Welsh
Series: 
Monographs on Statistics and Applied Probability 125
Publication Date: 
2012
Format: 
Hardcover
Category: 
Monograph

Introduction
Nature and role of sample surveys
Sample designs
Survey data, estimation and analysis
Why analysts of survey data should be interested in maximum likelihood estimation
Why statisticians should be interested in the analysis of survey data
A sample survey example
Maximum likelihood estimation for infinite populations
Bibliographic notes

Maximum likelihood theory for sample surveys
Introduction
Maximum likelihood using survey data
Illustrative examples with complete response
Dealing with nonresponse
Illustrative examples with nonresponse
Bibliographic notes

Alternative likelihood-based methods for sample survey data
Introduction
Pseudo-likelihood
Sample likelihood
Analytic comparisons of maximum likelihood, pseudolikelihood and sample likelihood estimation
The role of sample inclusion probabilities in analytic analysis
Bayesian analysis
Bibliographic notes

Populations with independent units
Introduction
The score and information functions for independent units
Bivariate Gaussian populations
Multivariate Gaussian populations
Non-Gaussian auxiliary variables
Stratified populations
Multinomial populations
Heterogeneous multinomial logistic populations
Bibliographic notes

Regression models
Introduction
A Gaussian example
Parameterization in the Gaussian model
Other methods of estimation
Non-Gaussian models
Different auxiliary variable distributions
Generalized linear models
Semiparametric and nonparametric methods
Bibliographic notes

Clustered populations
Introduction
A Gaussian group dependent model
A Gaussian group dependent regression model
Extending the Gaussian group dependent regression model
Binary group dependent models
Grouping models
Bibliographic notes

Informative nonresponse
Introduction
Nonresponse in innovation surveys
Regression with item nonresponse
Regression with arbitrary nonresponse
Imputation versus estimation
Bibliographic notes

Maximum likelihood in other complicated situations
Introduction
Likelihood analysis under informative selection
Secondary analysis of sample survey data
Combining summary population information with likelihood analysis
Likelihood analysis with probabilistically linked data
Bibliographic notes

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