Nonparametric bootstrap confidence intervals for variance components applied to interlaboratory comparisons

DOI10.1007/s13253-012-0087-9zbMath1302.62247OpenAlexW2034113102MaRDI QIDQ484601

Brent D. Burch

Publication date: 7 January 2015

Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13253-012-0087-9

zbMATH Keywords

methodone-way random effects modelbootstrap BC\(_a\)bootstrap standard methodsmall-sample adjustment

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12)

Related Items

Confidence distribution inferences in one-way random effects model, Robust confidence intervals for the difference of two independent population variances, Estimating kurtosis and confidence intervals for the variance under nonnormality, Improved Large-Sample Confidence Intervals for Ratios of Variance Components in Nonnormal Distributions

Uses Software

• WWGbook
• bootlib

Cites Work

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• Partially observed information and inference about non-Gaussian mixed linear models
• Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy
• Bootstrap confidence intervals. With comments and a rejoinder by the authors
• The jackknife and bootstrap
• REML estimation: Asymptotic behavior and related topics
• Assessing the performance of normal-based and REML-based confidence intervals for the intraclass correlation coefficient
• Generalized confidence intervals for proportions of total variance in mixed linear models
• Closed-Form Approximations to the REML Estimator of a Variance Ratio (or Heritability) in a Mixed Linear Model
• Confidence Intervals for a Variance Ratio, or for Heritability, in an Unbalanced Mixed Linear Model
• Better Bootstrap Confidence Intervals
• A Comparison of Variance Component Estimates for Arbitrary Underlying Distributions
• Adaptive Inference for the Two-Sample Scale Problem
• Exact Confidence Intervals for a Variance Ratio (or Heritability) in a Mixed Linear Model
• Stabilizing bootstrap‐t confidence intervals for small samples
• Making REML computationally feasible for large data sets: use of the Gibbs sampler
• Bootstrapping Robust Estimates for Clustered Data
• Bootstrap Methods