Open Access
Try, Try Again: Replication-Based Variance Estimation Methods for Survey Data Analysis in SAS ® 9.2
Pushpal K Mukhopadhyay,Anthony B. An,Randall D. Tobias,Donna L. Watts +3 more
- 01 Jan 2008
TL;DR: Replication methods are compared to the Taylor series expansion method with respect to both technical characteristics and practical utility, and other significant enhancements to the survey design and analysis procedures in SAS 9.2 are discussed.
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Abstract: Complex survey samples are constructed with selection schemes that affect the usual random assumptions, so SAS/STAT ® software provides specialized procedures to analyze them: SURVEYMEANS, SURVEYFREQ, SURVEYREG, and SURVEYLOGISTIC for means, frequencies, regression, and logistic analysis, respectively. These procedures all use the Taylor series expansion method for variance estimation, which is usually considered to be the "gold standard" when it is practical to compute. However, replication methods are also widely used in practice for variance estimation. Replication methods, such as the jackknife and balanced repeated replication (BRR), replace complex algebra with simple repeated analysis. They enable you to analyze the data without the original sample design, protecting survey security, and they ease the task of estimating variances for nonlinear quantities. With the release of SAS 9.2, the SAS/STAT survey analysis procedures now also implement replication methods. These include standard approaches such as jackknife and BRR as well as customized replication methods that employ usersupplied replicate weights. This paper discusses replication methods, comparing them to the Taylor series expansion method with respect to both technical characteristics and practical utility. This paper also discusses other significant enhancements to the survey design and analysis procedures in SAS 9.2.
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Carl-Erik Särndal,Bengt Swensson,Jan Wretman +2 more
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Jun Shao,Dongsheng Tu +1 more
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TL;DR: In this article, the authors proposed a method for estimating the variance of functions of means using the one-step jackknife, and showed that the method can be used to estimate the variance in the context of complex problems.
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Kirk M. Wolter
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TL;DR: The method of random groups and the Bootstrap method have been used for estimating variance in complex surveys as discussed by the authors, as well as the Jackknife method and Taylor series methods for generalized variance functions.
1.6K
Sampling: Design and Analysis
TL;DR: In his seminal book, Shewhart (1931) makes no demand on the distribution of the characteristic to be plotted on a control chart, so how can the idea that normality is, if not required, at least highly desirable be explained?
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