# Contributions to Survey Sampling and Applied Statistics

## Papers in Honor of H.O Hartley

- 1st Edition - January 1, 1978
- Author: H. O. Hartley
- Editor: H. A. David
- Language: English
- eBook ISBN:9 7 8 - 1 - 4 8 3 2 - 6 0 8 8 - 4

Contributions to Survey Sampling and Applied Statistics: Papers in Honor of H. O. Hartley covers the significant advances in survey sampling, modeling, and applied statistics. This… Read more

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Request a sales quoteContributions to Survey Sampling and Applied Statistics: Papers in Honor of H. O. Hartley covers the significant advances in survey sampling, modeling, and applied statistics. This book is organized into five parts encompassing 20 chapters. The opening part looks into some aspects of statistics, sampling, randomization, predictive estimation, and internal congruency. This part also considers the properties of variance estimation for a specified multiple frame survey design and some sampling designs involving unequal probabilities of selection and robust estimation of a finite population total. The next parts present the analysis and the theoretical and practical aspects of linear models, as well as the applications of time series analysis. These topics are followed by discussions of the testing for outliers in linear regression; the robustness of location estimators; and completeness comparisons among sample sequences. The closing part deals with the properties of norm estimators in regression and geometric programming. This part also provides tables of the normal conditioned on t-distribution. This book will prove useful to mathematicians and statisticians.

List of Contributors

Preface

Greetings to HOH for 1977

Published Works of H. O. Hartley

Part I Sampling

Laplace's Ratio Estimator

1. Introduction

2. The Survey and the Estimate

3. The Sampling Error: Standard Methods

4. Laplace's Analysis of the Sampling Error

References

Some Aspects of Statistics, Sampling, and Randomization

1. Introduction

2. The General Nature of Conventional Mathematical Statistics

3. What Is Inference?

4. The Finite Population Problem

5. The Labeled Case

6. The Matter of Labeling

7. Admissibility

8. Pivotality

9. Priors

10. Conclusion

References

Predictive Estimation and Internal Congruency

1. Introduction

2. Predictive Estimators

3. Model-Free Prediction

4. An Internally Congruent Ratio-Type Estimator

5. Some Sampling Investigations

6. Conclusions

Reference

Survey Statistics in Social Program Evaluation

1. Introduction

2. The Survey Role in Evaluation

3. The Evaluation Setting

4. The Use of Comparison Groups

5. Matching

6. Classification Versus Regression

7. Variable Sampling Weights

8. Summary

References

Variance Estimation for a Specified Multiple Frame Survey Design

1. Background

2. Estimation from Survey Data

3. Variance Estimates under Some Simplifying Assumptions

4. Generalized Estimates of Variance—To Provide Rough but Simply Computed Approximations

5. Evaluation of the Above Approximations Based on More Exact Variance Estimates

6. Composite Estimators

References

Sampling Designs Involving Unequal Probabilities of Selection and Robust Estimation of a Finite Population Total

1. Introduction

2. Unequal Probability Sampling without Replacement

3. Variance Estimators for ŶR in SRS

4. Robust Estimation of a Total

References

Selection Biases in Fixed Panel Surveys

1. Introduction

2. A Simple Two Category Model Repeated at Two Observation Times

3. Sampling at Three Observation Times

4. Summary Discussion

References

Sampling in Two or More Dimensions

1. Introduction

2. General Consideration

3. Specific Examples of Sampling Procedures

References

Part II The Linear Model

The Analysis of Linear Models with Unbalanced Data

1. Introduction

2. Computational Procedures

3. Two-Way Classification with Interaction

4. Two-Way Classification without Interaction

5. Two-Fold Nested Model

6. Summary

References

Nonhomogeneous Variances in the Mixed AOV Model; Maximum Likelihood Estimation

1. Introduction

2. The Mixed AOV Model with Unequal Error Variances

3. Constraining the Estimators

4. The General Algorithm—An Example

5. The Case of Proportional Variances

6. Measuring Instrument Models

7. The lt Algorithm for Balanced Data

8. The Missing Data Algorithm

References

Concurrency of Regression Equations with k Regressors

1. Introduction

2. Goodness of Fit of a Hypothetical Point of Concurrence

3. Test Statistics T02, T12, T22

4. Estimation of ξ and η

5. Test of Goodness of Fit of a Proposed ξ When η Is Known

References

A Univariate Formulation of the Multivariate Linear Model

1. The Vec Operator and Some Associated Results

2. The Model

3. Estimation

4. Independence under Normality

5. Hypothesis Testing

6. Jacobians

References

Multinomial Selection Index

1. Introduction

2. Estimation Procedure

3. Simulation Studies

4. Conclusions

References

Part III Time Series

Applications of Time Series Analysis

1. Introduction

2. Serial and Nonserial Models

3. A Canonical Analysis Useful for Detecting Contemporaneous and Other Relationships

4. Intervention Analysis for Detecting and Estimating Changes in Time Series

References

Part IV Outliers, Robustness, and Censoring

Testing for Outliers in Linear Regression

1. Introduction

2. On the Distribution of Rn

3. Equivalent Criteria for Single Outliers

4. Performance of Procedure for Identifying Single Outlier

5. Multiple Outlier Procedures

6. Example

7. Further Comments

References

Robustness of Location Estimators in the Presence of an Outlier

1. Introduction and Summary

2. Basic Theory

3. Outlying Population Differing in Location

4. Outlying Population Differing in Scale

5. Numerical Results in the Normal Cases

6. Concluding Remarks

Appendix

References

The Ninther, a Technique for Low-Effort Robust (Resistant) Location in Large Samples

1. Introduction

2. The Ninther

3. Distribution of Ninthers

4. Computing Effort

5. The Ninther-Median Combination

6. Impractically Large Data Sets

7. The Ninther-Mean Combination

8. A Comment

9. A Permutation Result

10. A Sampling Result

References

Completeness Comparisons among Sequences of Samples

1. Introduction

2. "Parametric" Test Procedures

3. Distribution-Free Tests

4. Some Other Problems

References

Part V Mathematical Programming and Computing

Absolute Deviations Curve Fitting: An Alternative to Least Squares

1. Introduction

2. M.A.D. Estimation and Geometric Programming

3. Properties of l1 Norm Estimators in Regression for Small Samples

4. Summary

Appendix

References

Tables of the Normal Conditioned on t-Distribution

1. Introduction

2. Model Development

3. Mathematical Development

References

Table 1

- No. of pages: 346
- Language: English
- Edition: 1
- Published: January 1, 1978
- Imprint: Academic Press
- eBook ISBN: 9781483260884

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