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A general and simple method for obtaining R2 from generalized linear mixed-effects models
Summary The use of both linear and generalized linear mixed-effects models (LMMs and GLMMs) has become popular not only in social and medical sciences, but also in biological sciences, especiallyExpand
Effect size, confidence interval and statistical significance: a practical guide for biologists
This article extensively discusses two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta‐analysis. Expand
Repeatability for Gaussian and non‐Gaussian data: a practical guide for biologists
Two types of repeatability (ordinary repeatability and extrapolated repeatability) are compared in relation to narrow‐sense heritability and two methods for calculating standard errors, confidence intervals and statistical significance are addressed. Expand
A farewell to Bonferroni: the problems of low statistical power and publication bias
The meta-analysis on statistical power by Jennions and Moller (2003) revealed that, in the field of behavioral ecology and animal behavior, statistical power of less than 20% to detect a small effect and power of more than 50% to detects a medium effect existed. Expand
A quantitative review of heterozygosity–fitness correlations in animal populations
It is shown that HFC studies do not generally reveal patterns predicted by population genetic theory, and are of small effect, and future studies should use more genetic marker data and utilize sampling designs that shed more light on the biological mechanisms that may modulate the strength of association. Expand
Redefine statistical significance
The default P-value threshold for statistical significance is proposed to be changed from 0.05 to 0.005 for claims of new discoveries in order to reduce uncertainty in the number of discoveries. Expand
Methodological issues and advances in biological meta-analysis
It is shown how the marriage between mixed-effects (hierarchical/multilevel) models and phylogenetic comparative methods has resolved most of the issues under discussion and how the use of within-study meta-analysis can improve many empirical studies typical of ecology and evolution. Expand
Missing inaction: the dangers of ignoring missing data.
It is shown how estimates of heritability and selection can be biased when the 'invisible fraction' (missing data due to mortality) is ignored, thus demonstrating the dangers of neglecting missing data in ecology and evolution. Expand
What determines species richness of parasitic organisms? A meta‐analysis across animal, plant and fungal hosts
Three universal predictors of parasite richness across host species are uncovered, namely host body size, geographical range size and population density, applicable regardless of the taxa considered and independently of most aspects of study design. Expand
Assessing the function of house sparrows' bib size using a flexible meta-analysis method
A flexible meta-analysis method is introduced that is better suited in the biological sciences than the methods usually employed in popular meta- analysis software because it accounts for a common form of nonindependence of the data. Expand