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Related Experiment Videos

A bootstrap approach to confidence regions for genetic parameters from Method R estimates

A Reverter1, C J Kaiser, C H Mallinckrodt

  • 1Animal Genetics and Breeding Unit, University of New England, Armidale, NSW, Australia.

Journal of Animal Science
|October 22, 1998
PubMed
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Bootstrapping techniques provide reliable confidence regions (CR) for heritability (h2) and permanent environmental effects (c2) even with limited Method R estimates. This method ensures accurate genetic parameter estimation in animal models.

Area of Science:

  • Quantitative Genetics
  • Animal Breeding
  • Statistical Genetics

Background:

  • Estimating heritability (h2) and permanent environmental effects (c2) is crucial in animal breeding.
  • Method R provides estimates, but computational demands can limit the number of replications.
  • Assessing the accuracy of confidence regions (CR) for these estimates is essential.

Purpose of the Study:

  • To evaluate bootstrapping techniques for generating confidence regions (CR) for heritability (h2) and permanent environmental effects (c2) using Method R estimates.
  • To determine the optimal number of subsamples (NUMEST) required for accurate CR estimation.
  • To compare the accuracy of parametric and nonparametric approaches for CR assessment.

Main Methods:

  • Simulated data from a univariate, repeated measures, full animal model with 50% subsampling.

Related Experiment Videos

  • Application of bootstrapping techniques to Method R estimates of h2 and c2.
  • Assessment of CR accuracy using parametric (bivariate normality) and nonparametric (rank deviations) methods.
  • Evaluation of average loss of confidence (LOSS) based on the number of estimates sampled (NUMEST).

    • Main Results:

    • Bootstrap estimates of h2 and c2 converged rapidly, within 10(-3) of asymptotic values at NUMEST = 5.
    • Similar convergence for standard error (SE) estimates was achieved with NUMEST = 20.
    • Nonparametric CR were more accurate than parametric CR at NUMEST < 10.
    • Parametric CR showed a faster rate of loss reduction with increasing NUMEST.

    Conclusions:

    • Bootstrapping techniques enable reliable confidence region (CR) estimation for heritability (h2) and permanent environmental effects (c2) even with a limited number of Method R estimates (e.g., 10-20).
    • This approach offers a computationally feasible solution for obtaining accurate genetic parameter estimates in complex animal models.
    • Both parametric and nonparametric methods can be employed, with the choice potentially depending on the number of available estimates.