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Nonparametric confidence interval estimators for heritability and expected selection response.

S J Knapp1, W C Bridges, M H Yang

  • 1Department of Crop Science, Oregon State University, Corvallis, Oregon 97331.

Genetics
|April 1, 1989
PubMed
Summary
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Jackknifing provides robust and unbiased statistical estimates for heritability (H) and selection response (R) intervals, especially when parametric methods fail. This nonparametric method is valuable for comparing estimates across different populations.

Area of Science:

  • Quantitative genetics
  • Statistical genetics
  • Biometrics

Background:

  • Statistical methods for comparing family-mean heritability (H) and expected selection response (R) estimates are underdeveloped.
  • Valid methods for estimating R intervals are also lacking.
  • Nonparametric methods like jackknifing offer alternatives when parametric methods are unsuitable or nonrobust.

Purpose of the Study:

  • To evaluate normal-approximation jackknife interval estimators for H and R.
  • To assess the robustness and accuracy of jackknife estimators under various distributions of between-family effects.

Main Methods:

  • Monte Carlo simulation was employed to generate data with normally distributed within-family effects and normal, uniform, or exponential between-family effects.
  • Jackknife interval estimators and parametric interval estimators were compared based on coverage probabilities.

Related Experiment Videos

  • Analysis of variance (ANOVA) estimates were also compared to parametric values.

    • Main Results:

    • Jackknife intervals for H and R demonstrated robust coverage probabilities, particularly when between-family effects were normally distributed.
    • Jackknife estimators for H and R were found to be unbiased when compared to parametric values.
    • ANOVA estimates for H and R showed significant underestimation, especially with smaller sample sizes.

    Conclusions:

    • Delete-one jackknifing is a versatile and effective statistical method for estimating H and R, offering robust and unbiased results.
    • Jackknifing is particularly valuable for hypothesis testing and comparing estimates between populations.
    • The study validates jackknifing as a reliable statistical tool in quantitative genetics research.