His primary areas of study are Cell biology, Ecology, Paraspeckles, Meta-analysis and Paraspeckle. His Cell biology research is multidisciplinary, relying on both RNA, RNA-binding protein, Cadherin and Cellular differentiation. His Ecology research includes elements of Demography and Akaike information criterion.
His Akaike information criterion research incorporates themes from Generalized linear model, Multilevel model, Imputation and Model selection. Shinichi Nakagawa usually deals with Multilevel model and limits it to topics linked to Econometrics and Information Criteria, Linear model, Goodness of fit, Explained variation and Statistical power. His Meta-analysis research incorporates elements of Ecology, Process, Field and Data science.
Ecology, Cell biology, Meta-analysis, Genetics and Demography are his primary areas of study. His work in Ecology covers topics such as Evolutionary biology which are related to areas like Quantitative genetics. In Cell biology, Shinichi Nakagawa works on issues like Paraspeckles, which are connected to Paraspeckle.
Much of his study explores Meta-analysis relationship to Cognitive psychology. His work on Genetics deals in particular with Gene and Epigenetics. His study in Demography is interdisciplinary in nature, drawing from both Offspring, Sexual selection, Mating, Mating system and Sparrow.
His primary areas of investigation include Meta-analysis, Cell biology, Ecology, Statistics and Paraspeckles. Shinichi Nakagawa has included themes like Sperm, Cognitive psychology, Perspective and Developmental psychology in his Meta-analysis study. The various areas that Shinichi Nakagawa examines in his Cell biology study include Polyadenylation, Downregulation and upregulation, RNA, Long non-coding RNA and Knockout mouse.
His biological study spans a wide range of topics, including Function and Intron. His work in the fields of Statistics, such as Repeatability, Covariate and Explained variation, intersects with other areas such as Variance and Anxiety. His Paraspeckles study integrates concerns from other disciplines, such as Ribonucleoprotein and Gene isoform.
His scientific interests lie mostly in Cell biology, Meta-analysis, Ecology, Paraspeckles and Ecology. His Cell biology research integrates issues from Knockout mouse, Gene expression and Alternative splicing. His Meta-analysis research includes themes of Zoology, Affect, Ambiguity, Judgement and Effect size.
His Ecology research is multidisciplinary, incorporating elements of Conservation science, Biodiversity, Range and Scientific progress. The study incorporates disciplines such as Paraspeckle, Compartmentalization and Gene isoform in addition to Paraspeckles. His work deals with themes such as Diversity, Biological system and Metagenomics, which intersect with Ecology.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A general and simple method for obtaining R2 from generalized linear mixed-effects models
Shinichi Nakagawa;Shinichi Nakagawa;Holger Schielzeth.
Methods in Ecology and Evolution (2013)
Effect size, confidence interval and statistical significance: a practical guide for biologists.
Shinichi Nakagawa;Innes C. Cuthill.
Biological Reviews (2007)
A farewell to Bonferroni: the problems of low statistical power and publication bias
Behavioral Ecology (2004)
Redefine statistical significance
Nature Human Behaviour (2018)
Multimodel inference in ecology and evolution: challenges and solutions
Journal of Evolutionary Biology (2011)
Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists.
Shinichi Nakagawa;Holger Schielzeth.
Biological Reviews (2010)
Meta-analysis and the science of research synthesis
Redefine Statistical Significance
Daniel Benjamin;James Berger;Magnus Johannesson;Brian Nosek.
Research Papers in Economics (2017)
The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded.
Shinichi Nakagawa;Shinichi Nakagawa;Paul C. D. Johnson;Holger Schielzeth.
Journal of the Royal Society Interface (2017)
rptR: repeatability estimation and variance decomposition by generalized linear mixed-effects models
Martin A. Stoffel;Martin A. Stoffel;Shinichi Nakagawa;Holger Schielzeth;Holger Schielzeth.
Methods in Ecology and Evolution (2017)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: