Estimation of Heritability for Samples from Non‐Normal Situations

Singhal, Raghav; Jain, J. P.

doi:10.1002/bimj.4710280514

Cited by 4 publications

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“…The results indicate that the heteroscedasticity introduces bias in the estimator. The effects of non-normality on the estimation of heritability estimation from half-sib model has been studied by Singhal and Jain (1986) and no study is Biometrical Journal 45 (2003) 5, 527-540 available regarding the behaviour of the conventional estimator of heritability under heteroscedasticity.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Heritability in Heteroscedastic One‐Way Unbalanced Random Model

Singh

2003

Biometrical J

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SummaryA modified estimator of heritability is proposed under heteroscedastic one way unbalanced random model. The distribution, moments and probability of permissible values (PPV) for conventional and modified estimators are derived. The behaviour of two estimators has been investigated, numerically, to devise a suitable estimator of heritability under variance heterogeneity. The numerical results reveal that under balanced case the heteroscedasticity affects the bias, MSE and PPV of conventional estimator, marginally. In case of unbalanced situations, the conventional estimator underestimates the parameter when more variable group has more observations and overestimates when more variable group has less observations, MSE of the conventional estimator decreases when more variable group has more observations and increases when more variable group has less observations and PPV is marginally decreased. The MSE and PPV are comparable for two estimators while the bias of modified estimator is less than the conventional estimator particularly for small and medium values of the parameter. These results suggest the use of modified estimator with equal or more observations for more variable group in presence of variance heterogeneity.

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Section: Introductionmentioning

confidence: 99%

Estimation of Heritability in Heteroscedastic One‐Way Unbalanced Random Model

Singh

2003

Biometrical J

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Confidence Limits on Heritability Under Non‐normal Variations

Singhal

1987

Biometrical J

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SunimaryMoment approximation for the non-normal sampling distribution of the ratio of mean squares in the balanced one-way Model I1 is found close to that of the Snedecor's F-distribution. The confidence limits for heritability of paternal half-sib correlations, derived employing F-distribution, are, in general, remarkably nerrow for platykurtic and wide for leptokurtic sire effecta than the normal limits. The effect of kurtosis of environmental deviations on t h w limits is of no consequence whereae the effect of skewness is invisible.K e y Words: Heritability ; Narrow and wide confidence intervals; Power of the test; Skewness and kurtosis.

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One-Way Classification

Sahai¹,

Ojeda²

2004

Analysis of Variance for Random Models

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Estimation of Heritability for Samples from Non‐Normal Situations

Cited by 4 publications

References 4 publications

Estimation of Heritability in Heteroscedastic One‐Way Unbalanced Random Model

Estimation of Heritability in Heteroscedastic One‐Way Unbalanced Random Model

Confidence Limits on Heritability Under Non‐normal Variations

One-Way Classification

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