Heritability, selection, and the response to selection in the presence of phenotypic measurement error: Effects, cures, and the role of repeated measurements
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Heritability, selection, and the response to selection in the presence of phenotypic measurement error: Effects, cures, and the role of repeated measurements
Authors
Keywords
-
Journal
EVOLUTION
Volume -, Issue -, Pages -
Publisher
Wiley
Online
2018-08-15
DOI
10.1111/evo.13573
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Fixed-effect variance and the estimation of repeatabilities and heritabilities: issues and solutions
- (2018) P. de Villemereuil et al. JOURNAL OF EVOLUTIONARY BIOLOGY
- Heritability analysis with repeat measurements and its application to resting-state functional connectivity
- (2017) Tian Ge et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population
- (2017) Timothée Bonnet et al. PLOS BIOLOGY
- General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models
- (2016) P. de Villemereuil et al. GENETICS
- Accounting for genetic differences among unknown parents in microevolutionary studies: how to include genetic groups in quantitative genetic animal models
- (2016) Matthew E. Wolak et al. JOURNAL OF ANIMAL ECOLOGY
- MCMC Methods for Multi-Response Generalized Linear Mixed Models: TheMCMCglmmRPackage
- (2015) Jarrod D. Hadfield Journal of Statistical Software
- QUANTITATIVE GENETIC MODELING AND INFERENCE IN THE PRESENCE OF NONIGNORABLE MISSING DATA
- (2014) Ingelin Steinsland et al. EVOLUTION
- Applications of Population Genetics to Animal Breeding, from Wright, Fisher and Lush to Genomic Prediction
- (2014) William G. Hill GENETICS
- Bayesian analysis of measurement error models using integrated nested Laplace approximations
- (2014) Stefanie Muff et al. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS
- UNIFICATION OF REGRESSION-BASED METHODS FOR THE ANALYSIS OF NATURAL SELECTION
- (2013) Michael B. Morrissey et al. EVOLUTION
- DISENTANGLING GENETIC AND PRENATAL SOURCES OF FAMILIAL RESEMBLANCE ACROSS ONTOGENY IN A WILD PASSERINE
- (2013) Jarrod D. Hadfield et al. EVOLUTION
- THE PREDICTION OF ADAPTIVE EVOLUTION: EMPIRICAL APPLICATION OF THE SECONDARY THEOREM OF SELECTION AND COMPARISON TO THE BREEDER’S EQUATION
- (2012) Michael B. Morrissey et al. EVOLUTION
- The danger of applying the breeder's equation in observational studies of natural populations
- (2010) M. B. MORRISSEY et al. JOURNAL OF EVOLUTIONARY BIOLOGY
- Phenotypic Complexity, Measurement Bias, and Poor Phenotypic Resolution Contribute to the Missing Heritability Problem in Genetic Association Studies
- (2010) Sophie van der Sluis et al. PLoS One
- An ecologist’s guide to the animal model
- (2009) Alastair J. Wilson et al. JOURNAL OF ANIMAL ECOLOGY
- Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
- (2009) Håvard Rue et al. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
- Why h2 does not always equal VA/VP?
- (2008) A. J. WILSON JOURNAL OF EVOLUTIONARY BIOLOGY
- Estimating evolutionary parameters when viability selection is operating
- (2008) J. D Hadfield PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
- Extra pair paternity in birds: a review of interspecific variation and adaptive function
- (2003) Simon C. Griffith et al. MOLECULAR ECOLOGY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started