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Statistical Computing: An Introduction to Data Analysis using S-Plus
TLDR
In this paper, the authors present a set of statistical models in S Plus, including the normal distribution, the central tendency, and the variance component analysis, as well as several other types of models.Abstract:
Preface.Statistical methods. Introduction to S Plus. Experimental design Central tendency. Probability. Variance. The Normal Distribution. Power calculations. Understanding data: graphical analysis. Understanding data: tabular analysis. Classical tests. Bootstrap and jackknife. Statistical models in S Plus. Regression. Analysis of variance. Analysis of covariance. Model criticism. Contrasts. Split plot Anova. Nested designs and variance components analysis. Graphs, functions and transformations. Curve fitting and piecewise regression. Non linear regression. Multiple regression. Model simplification. Probability distributions. Generalised linear models. Proportion data: binomial errors. Count data: Poisson errors. Binary response variables. Tree models. Non parametric smoothing. Survival analysis. Time series analysis. Mixed effects models. Spatial statistics. Bibliography. Index.read more
Citations
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Journal ArticleDOI
Generalized linear mixed models: a practical guide for ecology and evolution
Benjamin M. Bolker,Mollie Elizabeth Brooks,Connie J. Clark,Shane W. Geange,John R. Poulsen,M. Henry H. Stevens,Jada-Simone S. White +6 more
TL;DR: The use (and misuse) of GLMMs in ecology and evolution are reviewed, estimation and inference are discussed, and 'best-practice' data analysis procedures for scientists facing this challenge are summarized.
Journal ArticleDOI
Effect size, confidence interval and statistical significance: a practical guide for biologists.
TL;DR: 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.
Journal ArticleDOI
The delayed rise of present-day mammals
Olaf R. P. Bininda-Emonds,Olaf R. P. Bininda-Emonds,Marcel Cardillo,Kate E. Jones,Ross D. E. MacPhee,Robin M. D. Beck,Richard Grenyer,Samantha A. Price,Rutger A. Vos,John L. Gittleman,Andy Purvis +10 more
TL;DR: The results show that the phylogenetic ‘fuses’ leading to the explosion of extant placental orders are not only very much longer than suspected previously, but also challenge the hypothesis that the end-Cretaceous mass extinction event had a major, direct influence on the diversification of today’s mammals.
Journal ArticleDOI
Effects of sample size on the performance of species distribution models
TL;DR: In this article, a broad suite of algorithms with independent presence-absence data from multiple species and regions were evaluated for 46 species (from six different regions of the world) at three sample sizes (100, 30 and 10 records).
Journal ArticleDOI
Do not log-transform count data
Robert B. O'Hara,D. Johan Kotze +1 more
TL;DR: It is recommended that count data should not be analysed by log-transforming it, but instead models based on Poisson and negative binomial distributions should be used.