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  • Search: person:"Xie, Dawei"
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Cancer 1 Health Sciences 1 Krebskrankheit 1 Mathematics and Statistics 1 Medicine (General) 1 Public Health 1 Science 1 Social Sciences 1 Statistics and Numeric Data 1
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Free 1 Undetermined 1
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Article 3 Other 1
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Article in journal 1 Aufsatz in Zeitschrift 1
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Undetermined 3 English 1
Author
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Xie, Dawei 4 Davis, William W. 3 Parsons, Van L. 3 Raghunathan, Trivellore E. 3 Schenker, Nathaniel 3 Dodd, Kevin W. 2 Feuer, Eric J. 2 Lepkowski, James M. 1 Raghunathan, Trivellore 1
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Journal of the American Statistical Association : JASA 2 Journal of the American Statistical Association 1
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BASE 1 ECONIS (ZBW) 1 OLC EcoSci 1 RePEc 1
Showing 1 - 4 of 4
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Estimation of the proportion of overweight individuals in small areas—a robust extension of the Fay–Herriot model
Xie, Dawei; Raghunathan, Trivellore E.; Lepkowski, James M. - 2007
Hierarchical model such as Fay–Herriot (FH) model is often used in small area estimation. The method might perform well overall but is vulnerable to outliers. We propose a robust extension of the FH model by assuming the area random effects follow a t distribution with an unknown...
Persistent link: https://www.econbiz.de/10009477352
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Combining information from two surveys to estimate county-level prevalence rates of cancer risk factors and screening
Raghunathan, Trivellore; Xie, Dawei; Schenker, Nathaniel; … - In: Journal of the American Statistical Association : JASA 102 (2007) 478, pp. 474-486
Persistent link: https://www.econbiz.de/10003490292
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Combining Information From Two Surveys to Estimate County-Level Prevalence Rates of Cancer Risk Factors and Screening
Raghunathan, Trivellore E.; Xie, Dawei; Schenker, Nathaniel - In: Journal of the American Statistical Association 102 (2007) June, pp. 474-486
Persistent link: https://www.econbiz.de/10005238652
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Applications and Case Studies - Combining Information From Two Surveys to Estimate County-Level Prevalence Rates of Cancer Risk Factors and Screening
Raghunathan, Trivellore E.; Xie, Dawei; Schenker, Nathaniel - In: Journal of the American Statistical Association : JASA 102 (2007) 478, pp. 474-486
Persistent link: https://www.econbiz.de/10007741798
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