Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling.
The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, mirror-match bootstrap, and controlled sampling procedures. Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples. At the end of each chapter theoretical as well as numerical exercises are given which can help graduate students.
1. 2.1. Introduction - p. 23 2. 2.2. Definitions and Terminologies - p. 23 3. 2.3. Linear Unbiased Estimators - p. 25 4. 2.4. Properties of the Horvitz–Thompson Estimator - p. 29 5. 2.5. Nonexistence Theorems - p. 32 6. 2.6. Admissible Estimators - p. 37 7. 2.7. Sufficiency in Finite Population - p. 41 8. 2.8. Sampling Strategies - p. 47 9. 2.9. Discussions - p. 48 10. 2.10. Exercises - p. 49 11. Chapter 3. Simple Random Sampling - p. 51 12. 3.1. Introduction - p. 51 13. 3.2. Simple Random Sampling Without Replacement - p. 51 14. 3.3. Simple Random Sampling With Replacement - p. 68 15. 3.4. Interval Estimation - p. 74 16. 3.5. Determination of Sample Size - p. 76 17. 3.6. Inverse Sampling - p. 81 18. 3.7. Exercises - p. 84 19. Chapter 4. Systematic Sampling - p. 89 20. Chapter 5. Unequal Probability Sampling - p. 117 21. 5.1. Introduction - p. 117 22. 5.2. Probability Proportional to Size With Replacement Sampling Scheme - p. 118 23. 5.3. Probability Proportional to Size Without Replacement Sampling Scheme - p. 124 24. 5.4. Inclusion Probability Proportional to Measure of Size Sampling Scheme - p. 136 25. 5.5. Probability Proportional to Aggregate Size Without Replacement - p. 152 26. 5.6. Rao–Hartley–Cochran Sampling Scheme - p. 155 27. 5.7. Comparison of Unequal (Varying) Probability Sampling Designs - p. 161 28. 5.8. Exercises - p. 162 29. Chapter 6. Inference Under Superpopulation Model - p. 167 30. 6.1. Introduction - p. 167 31. 6.2. Definitions - p. 168 32. 6.3. Model-Assisted Inference - p. 170 33. 6.4. Model-Based Inference - p. 184 34. 6.5. Robustness of Designs and Predictors - p. 195 35. 6.6. Bayesian Inference - p. 200 36. 6.7. Comparison of Strategies Under Superpopulation Models - p. 204 37. 6.8. Discussions - p. 210 38. 6.9. Exercises - p. 211 39. Chapter 7. Stratified Sampling - p. 213 40. 7.1. Introduction - p. 213 41. 7.2. Definition of Stratified Sampling - p. 213 42. 7.3. Advantages of Stratified Sampling - p. 214 43. 7.4. Estimation Procedure - p. 214 44. 7.5. Allocation of Sample Size - p. 220 45. 7.6. Comparison Between Stratified and Unstratified Sampling - p. 225 46. 7.7. Construction of Strata - p. 233 47. 7.8. Estimation of Gain Due To Stratification - p. 240 48. 7.9. Poststratification - p. 247 49. 7.10. Exercises - p. 249 50. Chapter 8. Ratio Method of Estimation - p. 257 51. 8.1. Introduction - p. 257 52. 8.2. Ratio Estimator for Population Ratio - p. 257 53. 8.3. Ratio Estimator for Population Total - p. 264 54. 8.4. Biases and Mean-Square Errors for Specific Sampling Designs - p. 266 55. 8.5. Interval Estimation - p. 270 56. 8.6. Unbiased Ratio, Almost Unbiased Ratio, and Unbiased Ratio–Type Estimators - p. 273 57. 8.7. Ratio Estimator for Stratified Sampling - p. 275 58. 8.8. Ratio Estimator for Several Auxiliary Variables - p. 281 59. 8.9. Exercises - p. 283 60. Chapter 9. Regression, Product, and Calibrated Methods of Estimation - p. 287 61. 9.1. Introduction - p. 287 62. 9.2. Difference Estimator - p. 287 63. 9.3. Regression Estimator - p. 289 64. 9.4. Product Method of Estimation - p. 306 65. 9.5. Comparison Between the Ratio, Regression, Product, and Conventional Estimators - p. 311 66. 9.6. Dual to Ratio Estimator - p. 311 67. 9.7. Calibration Estimators - p. 313 68. 9.8. Exercises - p. 319 69. Appendix 9A - p. 322 70. Chapter 10. Two-Phase Sampling - p. 325 71. 10.1. Introduction - p. 325 72. 10.2. Two-Phase Sampling for Estimation - p. 326 73. 10.3. Two-Phase Sampling for Stratification - p. 345 74. 10.4. Two-Phase Sampling for Selection of Sample - p. 354 75. 10.5. Two-Phase Sampling for Stratification and Selection of Sample - p. 358 76. 10.6. Exercises - p. 362 77. Chapter 11. Repetitive Sampling - p. 367 78. 11.1. Introduction - p. 367 79. 11.2. Estimation of Mean for the Most Recent Occasion - p. 368 80. 11.3. Estimation of Change Over Two Occasions - p. 394 81. 11.4. Estimation of Mean of Means - p. 396 82. 11.5. Exercises - p. 402 83. Chapter 12. Cluster Sampling - p. 409 84. Chapter 13. Multistage Sampling - p. 423 85. 13.1. Introduction - p. 423 86. 13.2. Two-Stage Sampling Scheme - p. 424 87. 13.3. Estimation of the Population Total and Variance - p. 424 88. 13.4. First-Stage Units Are Selected by PPSWR Sampling Scheme - p. 430 89. 13.5. Modification of Variance Estimators - p. 435 90. 13.6. More than Two-Stage Sampling - p. 437 91. 13.7. Estimation of Mean per Unit - p. 439 92. 13.8. Optimum Allocation - p. 441 93. 13.9. Self -weighting Design - p. 444 94. 13.10. Exercises - p. 449 95. Chapter 14. Variance/Mean Square Estimation - p. 453 96. Chapter 15. Nonsampling Errors - p. 469 97. 15.1. Introduction - p. 469 98. 15.2. Sources of Nonsampling Errors - p. 469 99. 15.3. Controlling of Nonsampling Errors - p. 471 100. 15.4. Treatment of Nonresponse Error - p. 471 101. 15.5. Measurement Error - p. 493 102. 15.6. Exercises - p. 502 103. Chapter 16. Randomized Response Techniques - p. 505 104. 16.1. Introduction - p. 505 105. 16.2. Randomized Response Techniques for Qualitative Characteristics - p. 506 106. 16.3. Extension to More than One Categories - p. 513 107. 16.4. Randomized Response Techniques for Quantitative Characteristics - p. 515 108. 16.5. General Method of Estimation - p. 520 109. 16.6. Optional Randomized Response Techniques - p. 533 110. 16.7. Measure of Protection of Privacy - p. 539 111. 16.8. Optimality Under Superpopulation Model - p. 548 112. 16.9. Exercises - p. 553 113. Chapter 17. Domain and Small Area Estimation - p. 557 114. 17.1. Introduction - p. 557 115. 17.2. Domain Estimation - p. 558 116. 17.3. Small Area Estimation - p. 560 117. 17.4. Exercises - p. 583 118. Chapter 18. Variance Estimation: Complex Survey Designs - p. 587 119. 18.1. Introduction - p. 587 120. 18.2. Linearization Method - p. 587 121. 18.3. Random Group Method - p. 592 122. 18.4. Jackknife Method - p. 599 123. 18.5. Balanced Repeated Replication Method - p. 614 124. 18.6. Bootstrap Method - p. 629 125. 18.7. Generalized Variance Functions - p. 637 126. 18.8. Comparison Between the Variance Estimators - p. 640 127. 18.9. Exercises - p. 641 128. Chapter 19. Complex Surveys: Categorical Data Analysis - p. 645 129. 19.1. Introduction - p. 645 130. 19.2. Pearsonian Chi-Square Test for Goodness of Fit - p. 645 131. 19.3. Goodness of Fit for a General Sampling Design - p. 646 132. 19.4. Test of Independence - p. 661 133. 19.5. Tests of Homogeneity - p. 663 134. 19.6. Chi-Square Test Based on Superpopulation Model - p. 664 135. 19.7. Concluding Remarks - p. 667 136. 19.8. Exercises - p. 668 137. Chapter 20. Complex Survey Design: Regression Analysis - p. 673 138. Chapter 21. Ranked Set Sampling - p. 691 139. 21.1. Introduction - p. 691 140. 21.2. Ranked Set Sampling by Simple Random Sampling With Replacement Method - p. 691 141. 21.3. Simple Random Sampling Without Replacement - p. 708 142. 21.4. Size-Biased Probability of Selection - p. 716 143. 21.5. Concluding Remarks - p. 718 144. 21.6. Exercises - p. 719 145. Chapter 22. Estimating Functions - p. 723 146. 22.1. Introduction - p. 723 147. 22.2. Estimating Function and Estimating Equations - p. 723 148. 22.3. Estimating Function From Superpopulation Model - p. 727 149. 22.4. Estimating Function for a Survey Population - p. 731 150. 22.5. Interval Estimation - p. 737 151. 22.6. Nonresponse - p. 742 152. 22.7. Concluding Remarks - p. 744 153. 22.8. Exercises - p. 745 154. Chapter 23. Estimation of Distribution Functions and Quantiles - p. 747 155. 23.1. Introduction - p. 747 156. 23.2. Estimation of Distribution Functions - p. 747 157. 23.3. Estimation of Quantiles - p. 761 158. 23.4. Estimation of Median - p. 762 159. 23.5. Confidence Interval for Distribution Function and Quantiles - p. 767 160. 23.6. Concluding Remarks - p. 769 161. 23.7. Exercises - p. 770 162. Chapter 24. Controlled Sampling - p. 773 163. Chapter 25. Empirical Likelihood Method in Survey Sampling - p. 795 164. 25.1. Introduction - p. 795 165. 25.2. Scale Load Approach - p. 795 166. 25.3. Empirical Likelihood Approach - p. 797 167. 25.4. Empirical Likelihood for Simple Random Sampling - p. 798 168. 25.5. Pseudo–empirical Likelihood Method - p. 799 169. 25.6. Asymptotic Behavior of MPEL Estimator - p. 802 170. 25.7. Empirical Likelihood for Stratified Sampling - p. 804 171. 25.8. Model-Calibrated Pseudoempirical Likelihood - p. 809 172. 25.9. Pseudo–empirical Likelihood to Raking - p. 812 173. 25.10. Empirical Likelihood Ratio Confidence Intervals - p. 813 174. 25.11. Concluding Remarks - p. 818 175. 25.12. Exercises - p. 819 176. Chapter 26. Sampling Rare and Mobile Populations - p. 821 177. 26.1. Introduction - p. 821 178. 26.2. Screening - p. 822 179. 26.3. Disproportionate Sampling - p. 824 180. 26.4. Multiplicity or Network Sampling - p. 825 181. 26.5. Multiframe Sampling - p. 826 182. 26.6. Snowball Sampling - p. 837 183. 26.7. Location Sampling - p. 838 184. 26.8. Sequential Sampling - p. 839 185. 26.9. Adaptive Sampling - p. 840 186. 26.10. Capture–Recapture Method - p. 844 187. 26.11. Exercises - p. 856 188. Author Index - p. 883 189. Subject Index - p. 891
Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling.
The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, mirror-match bootstrap, and controlled sampling procedures. Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples. At the end of each chapter theoretical as well as numerical exercises are given which can help graduate students.
1. 2.1. Introduction - p. 23 2. 2.2. Definitions and Terminologies - p. 23 3. 2.3. Linear Unbiased Estimators - p. 25 4. 2.4. Properties of the Horvitz–Thompson Estimator - p. 29 5. 2.5. Nonexistence Theorems - p. 32 6. 2.6. Admissible Estimators - p. 37 7. 2.7. Sufficiency in Finite Population - p. 41 8. 2.8. Sampling Strategies - p. 47 9. 2.9. Discussions - p. 48 10. 2.10. Exercises - p. 49 11. Chapter 3. Simple Random Sampling - p. 51 12. 3.1. Introduction - p. 51 13. 3.2. Simple Random Sampling Without Replacement - p. 51 14. 3.3. Simple Random Sampling With Replacement - p. 68 15. 3.4. Interval Estimation - p. 74 16. 3.5. Determination of Sample Size - p. 76 17. 3.6. Inverse Sampling - p. 81 18. 3.7. Exercises - p. 84 19. Chapter 4. Systematic Sampling - p. 89 20. Chapter 5. Unequal Probability Sampling - p. 117 21. 5.1. Introduction - p. 117 22. 5.2. Probability Proportional to Size With Replacement Sampling Scheme - p. 118 23. 5.3. Probability Proportional to Size Without Replacement Sampling Scheme - p. 124 24. 5.4. Inclusion Probability Proportional to Measure of Size Sampling Scheme - p. 136 25. 5.5. Probability Proportional to Aggregate Size Without Replacement - p. 152 26. 5.6. Rao–Hartley–Cochran Sampling Scheme - p. 155 27. 5.7. Comparison of Unequal (Varying) Probability Sampling Designs - p. 161 28. 5.8. Exercises - p. 162 29. Chapter 6. Inference Under Superpopulation Model - p. 167 30. 6.1. Introduction - p. 167 31. 6.2. Definitions - p. 168 32. 6.3. Model-Assisted Inference - p. 170 33. 6.4. Model-Based Inference - p. 184 34. 6.5. Robustness of Designs and Predictors - p. 195 35. 6.6. Bayesian Inference - p. 200 36. 6.7. Comparison of Strategies Under Superpopulation Models - p. 204 37. 6.8. Discussions - p. 210 38. 6.9. Exercises - p. 211 39. Chapter 7. Stratified Sampling - p. 213 40. 7.1. Introduction - p. 213 41. 7.2. Definition of Stratified Sampling - p. 213 42. 7.3. Advantages of Stratified Sampling - p. 214 43. 7.4. Estimation Procedure - p. 214 44. 7.5. Allocation of Sample Size - p. 220 45. 7.6. Comparison Between Stratified and Unstratified Sampling - p. 225 46. 7.7. Construction of Strata - p. 233 47. 7.8. Estimation of Gain Due To Stratification - p. 240 48. 7.9. Poststratification - p. 247 49. 7.10. Exercises - p. 249 50. Chapter 8. Ratio Method of Estimation - p. 257 51. 8.1. Introduction - p. 257 52. 8.2. Ratio Estimator for Population Ratio - p. 257 53. 8.3. Ratio Estimator for Population Total - p. 264 54. 8.4. Biases and Mean-Square Errors for Specific Sampling Designs - p. 266 55. 8.5. Interval Estimation - p. 270 56. 8.6. Unbiased Ratio, Almost Unbiased Ratio, and Unbiased Ratio–Type Estimators - p. 273 57. 8.7. Ratio Estimator for Stratified Sampling - p. 275 58. 8.8. Ratio Estimator for Several Auxiliary Variables - p. 281 59. 8.9. Exercises - p. 283 60. Chapter 9. Regression, Product, and Calibrated Methods of Estimation - p. 287 61. 9.1. Introduction - p. 287 62. 9.2. Difference Estimator - p. 287 63. 9.3. Regression Estimator - p. 289 64. 9.4. Product Method of Estimation - p. 306 65. 9.5. Comparison Between the Ratio, Regression, Product, and Conventional Estimators - p. 311 66. 9.6. Dual to Ratio Estimator - p. 311 67. 9.7. Calibration Estimators - p. 313 68. 9.8. Exercises - p. 319 69. Appendix 9A - p. 322 70. Chapter 10. Two-Phase Sampling - p. 325 71. 10.1. Introduction - p. 325 72. 10.2. Two-Phase Sampling for Estimation - p. 326 73. 10.3. Two-Phase Sampling for Stratification - p. 345 74. 10.4. Two-Phase Sampling for Selection of Sample - p. 354 75. 10.5. Two-Phase Sampling for Stratification and Selection of Sample - p. 358 76. 10.6. Exercises - p. 362 77. Chapter 11. Repetitive Sampling - p. 367 78. 11.1. Introduction - p. 367 79. 11.2. Estimation of Mean for the Most Recent Occasion - p. 368 80. 11.3. Estimation of Change Over Two Occasions - p. 394 81. 11.4. Estimation of Mean of Means - p. 396 82. 11.5. Exercises - p. 402 83. Chapter 12. Cluster Sampling - p. 409 84. Chapter 13. Multistage Sampling - p. 423 85. 13.1. Introduction - p. 423 86. 13.2. Two-Stage Sampling Scheme - p. 424 87. 13.3. Estimation of the Population Total and Variance - p. 424 88. 13.4. First-Stage Units Are Selected by PPSWR Sampling Scheme - p. 430 89. 13.5. Modification of Variance Estimators - p. 435 90. 13.6. More than Two-Stage Sampling - p. 437 91. 13.7. Estimation of Mean per Unit - p. 439 92. 13.8. Optimum Allocation - p. 441 93. 13.9. Self -weighting Design - p. 444 94. 13.10. Exercises - p. 449 95. Chapter 14. Variance/Mean Square Estimation - p. 453 96. Chapter 15. Nonsampling Errors - p. 469 97. 15.1. Introduction - p. 469 98. 15.2. Sources of Nonsampling Errors - p. 469 99. 15.3. Controlling of Nonsampling Errors - p. 471 100. 15.4. Treatment of Nonresponse Error - p. 471 101. 15.5. Measurement Error - p. 493 102. 15.6. Exercises - p. 502 103. Chapter 16. Randomized Response Techniques - p. 505 104. 16.1. Introduction - p. 505 105. 16.2. Randomized Response Techniques for Qualitative Characteristics - p. 506 106. 16.3. Extension to More than One Categories - p. 513 107. 16.4. Randomized Response Techniques for Quantitative Characteristics - p. 515 108. 16.5. General Method of Estimation - p. 520 109. 16.6. Optional Randomized Response Techniques - p. 533 110. 16.7. Measure of Protection of Privacy - p. 539 111. 16.8. Optimality Under Superpopulation Model - p. 548 112. 16.9. Exercises - p. 553 113. Chapter 17. Domain and Small Area Estimation - p. 557 114. 17.1. Introduction - p. 557 115. 17.2. Domain Estimation - p. 558 116. 17.3. Small Area Estimation - p. 560 117. 17.4. Exercises - p. 583 118. Chapter 18. Variance Estimation: Complex Survey Designs - p. 587 119. 18.1. Introduction - p. 587 120. 18.2. Linearization Method - p. 587 121. 18.3. Random Group Method - p. 592 122. 18.4. Jackknife Method - p. 599 123. 18.5. Balanced Repeated Replication Method - p. 614 124. 18.6. Bootstrap Method - p. 629 125. 18.7. Generalized Variance Functions - p. 637 126. 18.8. Comparison Between the Variance Estimators - p. 640 127. 18.9. Exercises - p. 641 128. Chapter 19. Complex Surveys: Categorical Data Analysis - p. 645 129. 19.1. Introduction - p. 645 130. 19.2. Pearsonian Chi-Square Test for Goodness of Fit - p. 645 131. 19.3. Goodness of Fit for a General Sampling Design - p. 646 132. 19.4. Test of Independence - p. 661 133. 19.5. Tests of Homogeneity - p. 663 134. 19.6. Chi-Square Test Based on Superpopulation Model - p. 664 135. 19.7. Concluding Remarks - p. 667 136. 19.8. Exercises - p. 668 137. Chapter 20. Complex Survey Design: Regression Analysis - p. 673 138. Chapter 21. Ranked Set Sampling - p. 691 139. 21.1. Introduction - p. 691 140. 21.2. Ranked Set Sampling by Simple Random Sampling With Replacement Method - p. 691 141. 21.3. Simple Random Sampling Without Replacement - p. 708 142. 21.4. Size-Biased Probability of Selection - p. 716 143. 21.5. Concluding Remarks - p. 718 144. 21.6. Exercises - p. 719 145. Chapter 22. Estimating Functions - p. 723 146. 22.1. Introduction - p. 723 147. 22.2. Estimating Function and Estimating Equations - p. 723 148. 22.3. Estimating Function From Superpopulation Model - p. 727 149. 22.4. Estimating Function for a Survey Population - p. 731 150. 22.5. Interval Estimation - p. 737 151. 22.6. Nonresponse - p. 742 152. 22.7. Concluding Remarks - p. 744 153. 22.8. Exercises - p. 745 154. Chapter 23. Estimation of Distribution Functions and Quantiles - p. 747 155. 23.1. Introduction - p. 747 156. 23.2. Estimation of Distribution Functions - p. 747 157. 23.3. Estimation of Quantiles - p. 761 158. 23.4. Estimation of Median - p. 762 159. 23.5. Confidence Interval for Distribution Function and Quantiles - p. 767 160. 23.6. Concluding Remarks - p. 769 161. 23.7. Exercises - p. 770 162. Chapter 24. Controlled Sampling - p. 773 163. Chapter 25. Empirical Likelihood Method in Survey Sampling - p. 795 164. 25.1. Introduction - p. 795 165. 25.2. Scale Load Approach - p. 795 166. 25.3. Empirical Likelihood Approach - p. 797 167. 25.4. Empirical Likelihood for Simple Random Sampling - p. 798 168. 25.5. Pseudo–empirical Likelihood Method - p. 799 169. 25.6. Asymptotic Behavior of MPEL Estimator - p. 802 170. 25.7. Empirical Likelihood for Stratified Sampling - p. 804 171. 25.8. Model-Calibrated Pseudoempirical Likelihood - p. 809 172. 25.9. Pseudo–empirical Likelihood to Raking - p. 812 173. 25.10. Empirical Likelihood Ratio Confidence Intervals - p. 813 174. 25.11. Concluding Remarks - p. 818 175. 25.12. Exercises - p. 819 176. Chapter 26. Sampling Rare and Mobile Populations - p. 821 177. 26.1. Introduction - p. 821 178. 26.2. Screening - p. 822 179. 26.3. Disproportionate Sampling - p. 824 180. 26.4. Multiplicity or Network Sampling - p. 825 181. 26.5. Multiframe Sampling - p. 826 182. 26.6. Snowball Sampling - p. 837 183. 26.7. Location Sampling - p. 838 184. 26.8. Sequential Sampling - p. 839 185. 26.9. Adaptive Sampling - p. 840 186. 26.10. Capture–Recapture Method - p. 844 187. 26.11. Exercises - p. 856 188. Author Index - p. 883 189. Subject Index - p. 891
