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Using R for variance estimation in social surveys Eleanor Law, ONSOutline Complex sample design and impact on variance of estimates The linearised jackknife method Implementation of the linearised
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What is jackknifing for variance components?
Jackknifing for variance components is a resampling technique used in statistics to estimate the variance and bias of estimators by systematically leaving out one or more observations from the dataset.
Who is required to file jackknifing for variance components?
Researchers and statisticians who use jackknifing methods in their analysis to report variance components in their studies may be required to document their methods and results.
How to fill out jackknifing for variance components?
To fill out jackknifing for variance components, one must outline the statistical model used, the data points omitted, the calculations of variance components, and any assumptions made during the analysis.
What is the purpose of jackknifing for variance components?
The purpose of jackknifing for variance components is to provide a more accurate estimation of variance and to assess the stability of statistical estimators in the presence of data variability.
What information must be reported on jackknifing for variance components?
Information to be reported includes the dataset used, the number of observations left out, the calculated variance components, and the confidence intervals for the estimates.
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