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Unbalancedness under RSS-structured Cluster Randomized Designs : RSS 구조화된 무작위 군집 설계에서의 불균형성
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 임요한 | - |
dc.contributor.advisor | Xinlei Wang | - |
dc.contributor.author | 안수현 | - |
dc.date.accessioned | 2017-07-14T00:31:43Z | - |
dc.date.available | 2017-07-14T00:31:43Z | - |
dc.date.issued | 2016-02 | - |
dc.identifier.other | 000000132241 | - |
dc.identifier.uri | https://hdl.handle.net/10371/121156 | - |
dc.description | 학위논문 (박사)-- 서울대학교 대학원 : 통계학과, 2016. 2. Xinlei Wang. | - |
dc.description.abstract | In this thesis, we consider unbalancedness under cluster randomized designs (CRDs) using ranked set sampling (RSS), and extend nonparametric inference procedures, previously developed by Wang et al. (2016) for the use of balanced RSS (BRSS) with CRDs, to account for the unbalanced structures. The unbalanced structures are from (i) the use of unbalanced ranked set sampling (URSS) with CRDs or (ii) the use of BRSS with CRDs having unbalancedly sized groups. First, we consider URSS-structured CRDs. We theoretically study the URSS estimators of the treatment effect and numerically compare the relative effciency of the URSS vs. BRSS estimators. We also study and compare the power of the URSS tests vs. their BRSS counterparts via simulation. Second, we consider BRSS-structured CRDs having unbalancedly sized groups. We modify and improve the BRSS tests in Wang et al. (2016) and compare power of the modified BRSS tests vs. their original BRSS counterparts via simulation. Further, we illustrate each inference procedure with a data example using an educational data. Finally, we offer flexibility of incorporating RSS in CRDs in practice. | - |
dc.description.tableofcontents | Chapter 1 Introduction 1
Chapter 2 Cluster Randomized Designs with URSS Data Structures 4 2.1 Introduction 4 2.2 Notation for data from URSS-structured CRDs 9 2.3 Estimating Treatment Effect 11 2.3.1 URSS estimators 11 2.3.2 Optimality, unbiasedness and variance 13 2.3.3 Relative eciency 18 2.4 Testing Treatment Effect 27 2.4.1 Asymptotic properties 27 2.4.2 Asymptotic pivotal method 36 2.4.3 Power comparison 40 2.5 Missing Data 46 2.6 Data Example 49 2.7 Conclusion 54 Chapter 3 Unbalancedly Sized Groups in Ranked Set Sampling for Cluster Randomized Design 56 3.1 Introduction 56 3.2 Review the BRSS-structured CRDs 59 3.3 Pooled Variance Estimator 62 3.4 Power Comparison 66 3.5 Data Example 72 3.6 Conclusion 74 Chapter 4 Conclusion 76 Bibliography 78 Appendix 80 Abstract (in Korean) 83 | - |
dc.format | application/pdf | - |
dc.format.extent | 3363755 bytes | - |
dc.format.medium | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject | Hierarchical linear models | - |
dc.subject | missing data | - |
dc.subject | Neyman allocation | - |
dc.subject | nonparametric inference | - |
dc.subject | relative efficiency | - |
dc.subject | treatment effect | - |
dc.subject | unbalanced ranked set sampling | - |
dc.subject.ddc | 519 | - |
dc.title | Unbalancedness under RSS-structured Cluster Randomized Designs | - |
dc.title.alternative | RSS 구조화된 무작위 군집 설계에서의 불균형성 | - |
dc.type | Thesis | - |
dc.description.degree | Doctor | - |
dc.citation.pages | 83 | - |
dc.contributor.affiliation | 자연과학대학 통계학과 | - |
dc.date.awarded | 2016-02 | - |
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