The BLUPs are not "best" when it comes to bootstrapping
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Cited by:
- Paul Anand & Jere R. Behrman & Hai‐Anh H. Dang & Sam Jones, 2019.
"Does sorting matter for learning inequality?: Evidence from East Africa,"
WIDER Working Paper Series
wp-2019-110, World Institute for Development Economic Research (UNU-WIDER).
- Paul Anand & Jere R. Behrman & Hai-Anh H. Dang & Sam Jones, 2019. "Does sorting matter for learning inequality?Evidence from East Africa," PIER Working Paper Archive 20-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Shang, Junfeng & Cavanaugh, Joseph E., 2008. "Bootstrap variants of the Akaike information criterion for mixed model selection," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2004-2021, January.
- Flores-Agreda, Daniel & Cantoni, Eva, 2019. "Bootstrap estimation of uncertainty in prediction for generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 130(C), pages 1-17.
- Brian Gray & Vyacheslav Lyubchich & Yulia Gel & James Rogala & Dale Robertson & Xiaoqiao Wei, 2016. "Estimation of river and stream temperature trends under haphazard sampling," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 89-105, March.
- Shang, Junfeng & Cavanaugh, Joseph E., 2008. "An assumption for the development of bootstrap variants of the Akaike information criterion in mixed models," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1422-1429, September.
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Keywords
Bootstrap Correlated data Mixed models Nested models;Statistics
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