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Table of Contents
Intro
Preface
Contents
Acronyms
1 Small Area Estimation
1.1 Introduction
1.2 Mixed Models
1.3 The Data Files
1.3.1 The LFS Data Files
1.3.2 The LCS Data Files
References
2 Design-Based Direct Estimation
2.1 Introduction
2.2 Survey Sampling Theory
2.3 Direct Estimator of the Total and the Mean
2.4 Estimator of the Ratio
2.5 Other Direct Estimators of the Mean and the Total
2.6 Bootstrap Resampling for Variance Estimation
2.7 Jackknife Resampling for Variance Estimation
2.7.1 Delete-One-Cluster Jackknife for Estimators of Domain Parameters
2.8 R Codes for Design-Based Direct Estimators
2.8.1 Horvitz-Thompson Direct Estimators of the Total and the Mean
2.8.2 Hájek Direct Estimator of the Mean and the Total
2.8.3 Jackknife Estimator of Variances
2.8.4 Functions for Calculating Direct Estimators
References
3 Design-Based Indirect Estimation
3.1 Introduction
3.2 Basic Synthetic Estimator
3.3 Post-Stratified Estimator
3.4 Sample Size Dependent Estimator
3.5 Generalized Regression Estimator
3.6 Estimators of Unemployment Rates
3.7 A Labor Force Survey
3.7.1 Weight Calibration and Benchmarking
3.7.2 Resampling Methods for the LFS
3.8 R Codes for Design-Based Indirect Estimators
3.8.1 Basic Synthetic Estimator of the Total
3.8.2 Post-stratified Estimator of the Total
3.8.3 Generalized Regression Estimator of the Mean
References
4 Prediction Theory
4.1 Introduction
4.2 The Predictive Approach
4.3 Prediction Theory Under the Linear Model
4.4 The General Prediction Theorem
4.5 BLUPs for Some Simple Models
4.6 R Codes for BLUPs
References
5 Linear Models
5.1 Introduction
6.4 Maximum Likelihood Estimation
6.4.1 Description of the Method
6.4.2 Maximum Likelihood Estimators for Alternative Parameters
6.5 Residual Maximum Likelihood Estimation
6.5.1 Description of the Method
6.5.2 REML Estimators for Alternative Parameters
6.5.3 Further REML Equations for Linear Mixed Models
6.6 Henderson 3 Estimation
6.6.1 Description of the Method
6.6.2 Moments of Henderson 3 Estimators
6.7 R Codes for Fitting Linear Mixed Models
6.7.1 Library lme4
6.7.2 Library nlme
References
7 Nested Error Regression Models
7.1 Introduction
Preface
Contents
Acronyms
1 Small Area Estimation
1.1 Introduction
1.2 Mixed Models
1.3 The Data Files
1.3.1 The LFS Data Files
1.3.2 The LCS Data Files
References
2 Design-Based Direct Estimation
2.1 Introduction
2.2 Survey Sampling Theory
2.3 Direct Estimator of the Total and the Mean
2.4 Estimator of the Ratio
2.5 Other Direct Estimators of the Mean and the Total
2.6 Bootstrap Resampling for Variance Estimation
2.7 Jackknife Resampling for Variance Estimation
2.7.1 Delete-One-Cluster Jackknife for Estimators of Domain Parameters
2.8 R Codes for Design-Based Direct Estimators
2.8.1 Horvitz-Thompson Direct Estimators of the Total and the Mean
2.8.2 Hájek Direct Estimator of the Mean and the Total
2.8.3 Jackknife Estimator of Variances
2.8.4 Functions for Calculating Direct Estimators
References
3 Design-Based Indirect Estimation
3.1 Introduction
3.2 Basic Synthetic Estimator
3.3 Post-Stratified Estimator
3.4 Sample Size Dependent Estimator
3.5 Generalized Regression Estimator
3.6 Estimators of Unemployment Rates
3.7 A Labor Force Survey
3.7.1 Weight Calibration and Benchmarking
3.7.2 Resampling Methods for the LFS
3.8 R Codes for Design-Based Indirect Estimators
3.8.1 Basic Synthetic Estimator of the Total
3.8.2 Post-stratified Estimator of the Total
3.8.3 Generalized Regression Estimator of the Mean
References
4 Prediction Theory
4.1 Introduction
4.2 The Predictive Approach
4.3 Prediction Theory Under the Linear Model
4.4 The General Prediction Theorem
4.5 BLUPs for Some Simple Models
4.6 R Codes for BLUPs
References
5 Linear Models
5.1 Introduction
6.4 Maximum Likelihood Estimation
6.4.1 Description of the Method
6.4.2 Maximum Likelihood Estimators for Alternative Parameters
6.5 Residual Maximum Likelihood Estimation
6.5.1 Description of the Method
6.5.2 REML Estimators for Alternative Parameters
6.5.3 Further REML Equations for Linear Mixed Models
6.6 Henderson 3 Estimation
6.6.1 Description of the Method
6.6.2 Moments of Henderson 3 Estimators
6.7 R Codes for Fitting Linear Mixed Models
6.7.1 Library lme4
6.7.2 Library nlme
References
7 Nested Error Regression Models
7.1 Introduction