A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase
The bootstrap method is often used for variance estimation in sample surveys with a stratified multistage sampling design. It is typically implemented by producing a set of bootstrap weights that is made available to users and that accounts for the complexity of the sampling design. The Rao–Wu–Yue m...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Stats |
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| Online Access: | https://www.mdpi.com/2571-905X/5/2/19 |
| _version_ | 1797482200344559616 |
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| author | Jean-François Beaumont Nelson Émond |
| author_facet | Jean-François Beaumont Nelson Émond |
| author_sort | Jean-François Beaumont |
| collection | DOAJ |
| description | The bootstrap method is often used for variance estimation in sample surveys with a stratified multistage sampling design. It is typically implemented by producing a set of bootstrap weights that is made available to users and that accounts for the complexity of the sampling design. The Rao–Wu–Yue method is often used to produce the required bootstrap weights. It is valid under stratified with-replacement sampling at the first stage or fixed-size without-replacement sampling provided the first-stage sampling fractions are negligible. Some surveys use designs that do not satisfy these conditions. We propose a simple and unified bootstrap method that addresses this limitation of the Rao–Wu–Yue bootstrap weights. This method is applicable to any multistage sampling design as long as valid bootstrap weights can be produced for each distinct stage of sampling. Our method is also applicable to two-phase sampling designs provided that Poisson sampling is used at the second phase. We use this design to model survey nonresponse and derive bootstrap weights that account for nonresponse weighting. The properties of our bootstrap method are evaluated in three limited simulation studies. |
| first_indexed | 2024-03-09T22:28:51Z |
| format | Article |
| id | doaj.art-52559743daaf4e6b8878feeeab50392b |
| institution | Directory Open Access Journal |
| issn | 2571-905X |
| language | English |
| last_indexed | 2024-03-09T22:28:51Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Stats |
| spelling | doaj.art-52559743daaf4e6b8878feeeab50392b2023-11-23T19:00:08ZengMDPI AGStats2571-905X2022-03-015233935710.3390/stats5020019A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second PhaseJean-François Beaumont0Nelson Émond1Statistics Canada, Ottawa, ON K1A 0T6, CanadaStatistics Canada, Ottawa, ON K1A 0T6, CanadaThe bootstrap method is often used for variance estimation in sample surveys with a stratified multistage sampling design. It is typically implemented by producing a set of bootstrap weights that is made available to users and that accounts for the complexity of the sampling design. The Rao–Wu–Yue method is often used to produce the required bootstrap weights. It is valid under stratified with-replacement sampling at the first stage or fixed-size without-replacement sampling provided the first-stage sampling fractions are negligible. Some surveys use designs that do not satisfy these conditions. We propose a simple and unified bootstrap method that addresses this limitation of the Rao–Wu–Yue bootstrap weights. This method is applicable to any multistage sampling design as long as valid bootstrap weights can be produced for each distinct stage of sampling. Our method is also applicable to two-phase sampling designs provided that Poisson sampling is used at the second phase. We use this design to model survey nonresponse and derive bootstrap weights that account for nonresponse weighting. The properties of our bootstrap method are evaluated in three limited simulation studies.https://www.mdpi.com/2571-905X/5/2/19bootstrap weightstwo-stage samplingmultistage samplingnon-negligible sampling fractiontwo-phase samplingnonresponse |
| spellingShingle | Jean-François Beaumont Nelson Émond A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase Stats bootstrap weights two-stage sampling multistage sampling non-negligible sampling fraction two-phase sampling nonresponse |
| title | A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase |
| title_full | A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase |
| title_fullStr | A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase |
| title_full_unstemmed | A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase |
| title_short | A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase |
| title_sort | bootstrap variance estimation method for multistage sampling and two phase sampling when poisson sampling is used at the second phase |
| topic | bootstrap weights two-stage sampling multistage sampling non-negligible sampling fraction two-phase sampling nonresponse |
| url | https://www.mdpi.com/2571-905X/5/2/19 |
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