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Complex methods, including the use of sampling weights and replication methods for variance estimation, are therefore required for data analysis.
Pepe et al. [ 12] further investigated methods for variance estimation based on the bootstrap but found the performance unsatisfactory.
We used Taylor series estimation methods for variance estimation (STATA svy commands) to obtain proper standard error estimates for the cross-tabulations and logistic regressions [ 27].
The approximate methods for variance estimation have been becoming popular for cross-sectional and longitudinal complex survey data analysis, and their properties have been investigated theoretically and empirically [ 33].
Weighted means, frequencies and logistic regressions were computed using Statistical Analysis System SASSurveyvey Procedures in SAS V.9.2, 18 which adjusted for the characteristics of the complex survey design using jackknife repeated replication methods for variance estimation.
Potential improvements include alternative methods for variance stabilization transformations (in contrast to the log transformation used in this case) and other normalization methods, for example, GC content correction methods and scaling methods like Trimmed mean of M values.
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In the past several years there has been considerable commercial and academic interest in methods for variance-based sensitivity analysis.
This resulted in a two weight scheme which is known to produce a pronounced weight growth problem which rapidly makes it inefficient as a control variate method for variance reduction.
Background correction, between-array normalization and transformation were carried out using the VSN method for variance stabilization and calibration of microarray data.
All the analyses took the form of weighted statistics with their 95% confidence intervals using the Taylor series linearization method for variance estimation [ 23].
We then applied complex survey data analysis command designating variables that contain information about the survey design, sampling unit (villages) and specifying the default method for variance estimation method.
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