ArticleGenetics, selection, evolution : GSE2018
Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method.
Article in Genetics, selection, evolution : GSE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 149 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
149 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Transition from Conventional to Genomic Selection (ssGBLUP) led to improve in accuracy gains and selection decisions in Sahiwal Cattle.Scientific reports · 2026Article
- Validation of a national genetic evaluation for methane emission in Holstein cattle.JDS communications · 2026Article
- Better Multi-Breed Genomic Predictions for Tropical Bull Fertility Using a Breed-Adjusted Genomic Relationship Matrix.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Genomic selection and association analyses for improving semen traits in Thai native roosters.Poultry science · 2026Article
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- Contribution of Fat Adjustment to Residual Feed Intake Estimation in Beef Cattle.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Genomic Prediction and Genome-Wide Association Analysis of Egg Fertility and Hatchability Traits in Thai Native Grandparent Stock.Animals : an open access journal from MDPI · 2026Article
- Random forest imputation and genomic prediction for missing egg production time-series data in yellow-feathered broiler breeders.BMC genomics · 2026Article
- Genetic Evaluation of Beef Sires Using a Beef-on-Dairy Crossbred Reference Population.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Accuracy of single-step genomic selection for egg production in yellow-feathered broilers using a random regression model.Poultry science · 2026Article
- Genomic Prediction Ability Using Linear and Threshold Approaches for Different Stayability Definitions in Nellore Females.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Impact of Model Parameterisation and Variance Component Estimates on Genomic Predictions of Carcass Traits in Montana Composite Cattle.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Genomic selection accuracy and bias using imputed genotypes on growth, welfare and fitness traits in two Pekin duck lines.BMC genomics · 2026Article
- Genomic Prediction Ability for Novel Profitability Traits Using Different Models in Nelore Cattle.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Sharing approaches in predictive genomics across animals, plants and humans.Nature genetics · 2026Review
89 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
Abstract
backgroundCross-validation tools are used increasingly to validate and compare genetic evaluation methods but analytical properties of cross-validation methods are rarely described. There is also a lack of cross-validation tools for complex problems such as prediction of indirect effects (e.g. maternal effects) or for breeding schemes with small progeny group sizes.
resultsWe derive the expected value of several quadratic forms by comparing genetic evaluations including "partial" and "whole" data. We propose statistics that compare genetic evaluations including "partial" and "whole" data based on differences in means, covariance, and correlation, and term the use of these statistics "method LR" (from linear regression). Contrary to common belief, the regression of true on estimated breeding values is (on expectation) lower than 1 for small or related validation sets, due to family structures. For validation sets that are sufficiently large, we show that these statistics yield estimators of bias, slope or dispersion, and population accuracy for estimated breeding values. Similar results hold for prediction of future phenotypes although we show that estimates of bias, slope or dispersion using prediction of future phenotypes are sensitive to incorrect heritabilities or precorrection for fixed effects. We present an example for a set of 2111 Brahman beef cattle for which, in repeated partitioning of the data into training and validation sets, there is very good agreement of statistics of method LR with prediction of future phenotypes.
conclusionsAnalytical properties of cross-validation measures are presented. We present a new method named LR for cross-validation that is automatic, easy to use, and which yields the quantities of interest. The method compares predictions based on partial and whole data, which results in estimates of accuracy and biases. Prediction of observed records may yield biased results due to precorrection or use of incorrect heritabilities.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.