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"Multiple comparisons (Statistics)"
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Multiple Comparisons Using R
Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. Adopting a unifying theme based on maximum statistics, this self-contained introduction describes the common underlying theory of multiple comparison procedures through numerous examples. It covers a range of multiple comparison procedures, from the Bonferroni method and Simes' test to resampling and adaptive design methods. The book also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org.
eBook
Visualization and Verbalization of Data
This volume shows how correspondence analysis and related techniques enable the display of data in graphical form, which results in the verbalization of the structures in data. Renowned researchers in the field trace the history of these techniques and cover their current applications. Examples include the spatial visualization of multivariate data, cluster analysis in computer science, the transformation of a textual data set into numerical data, the use of quantitative and qualitative variables in multiple factor analysis, and more.
eBook
Making multiple comparisons easy: a decision tree and visual statistics guide for data with more than two groups
Abstract
Many scientists learn during training to use analysis of variance (ANOVA) when comparing more than 2 groups, yet the principles and follow-up steps are often not well explained. This overview provides a practical guide for selecting appropriate multiple comparisons tests and for interpreting and presenting data accurately. While not exhaustive, it highlights commonly used approaches, many of which are available in GraphPad Prism, a widely used statistical program among cell and molecular biologists. The authors have no affiliation with Dotmatics, the distributor of GraphPad Prism, and this overview is not intended as an endorsement of the software.
Journal Article
A theory of contrasts for modified Freeman–Tukey statistics and its applications to Tukey’s post-hoc tests for contingency tables
This paper presents a theory of contrasts designed for modified Freeman–Tukey (FT) statistics which are derived through square-root transformations of observed frequencies (proportions) in contingency tables. Some modifications of the original FT statistic are necessary to allow for ANOVA-like exact decompositions of the global goodness of fit (GOF) measures. The square-root transformations have an important effect of stabilizing (equalizing) variances. The theory is then used to derive Tukey’s post-hoc pairwise comparison tests for contingency tables. Tukey’s tests are more restrictive, but are more powerful, than Scheffè’s post-hoc tests developed earlier for the analysis of contingency tables. Throughout this paper, numerical examples are given to illustrate the theory. Modified FT statistics, like other similar statistics for contingency tables, are based on a large-sample rationale. Small Monte-Carlo studies are conducted to investigate asymptotic (and non-asymptotic) behaviors of the proposed statistics.
Journal Article
Programming Graphical User Interfaces in R
Focusing on graphic user interfaces (GUIs) within the R language, this book shows programmers and users how to develop their own GUIs, enabling them to interface with other languages. The text opens the possibilities of R's huge and growing set of statistical methods. The authors cover four different packages for writing GUIs: gWidgets, RGtk2, Qt, and Tcl Tk. Supported by a package in CRAN that contains all of the code along with additional examples, the text is filled with numerous examples ranging from the very simple to detailed illustrations of how to code actual interfaces.
eBook