The null hypothesis significance test in health sciences research (1995-2006): statistical analysis and interpretation

<p>Abstract</p> <p>Background</p> <p>The null hypothesis significance test (NHST) is the most frequently used statistical method, although its inferential validity has been widely criticized since its introduction. In 1988, the <it>International Committee of Medical Journal Editors </it>(ICMJE) warned against sole reliance on NHST to substantiate study conclusions and suggested supplementary use of confidence intervals (CI). Our objective was to evaluate the extent and quality in the use of NHST and CI, both in English and Spanish language biomedical publications between 1995 and 2006, taking into account the <it>International Committee of Medical Journal Editors </it>recommendations, with particular focus on the accuracy of the interpretation of statistical significance and the validity of conclusions.</p> <p>Methods</p> <p>Original articles published in three English and three Spanish biomedical journals in three fields (General Medicine, Clinical Specialties and Epidemiology - Public Health) were considered for this study. Papers published in 1995-1996, 2000-2001, and 2005-2006 were selected through a systematic sampling method. After excluding the purely descriptive and theoretical articles, analytic studies were evaluated for their use of NHST with P-values and/or CI for interpretation of statistical "significance" and "relevance" in study conclusions.</p> <p>Results</p> <p>Among 1,043 original papers, 874 were selected for detailed review. The exclusive use of P-values was less frequent in English language publications as well as in Public Health journals; overall such use decreased from 41% in 1995-1996 to 21% in 2005-2006. While the use of CI increased over time, the "significance fallacy" (to equate statistical and substantive significance) appeared very often, mainly in journals devoted to clinical specialties (81%). In papers originally written in English and Spanish, 15% and 10%, respectively, mentioned statistical significance in their conclusions.</p> <p>Conclusions</p> <p>Overall, results of our review show some improvements in statistical management of statistical results, but further efforts by scholars and journal editors are clearly required to move the communication toward ICMJE advices, especially in the clinical setting, which seems to be imperative among publications in Spanish.</p

Environmental Predictors of Diversity in Recent Planktonic Foraminifera as Recorded in Marine Sediments

© 2016 Fenton et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. [4.0 license]. The attached file is the published version of the article

Variation in Symbiodinium ITS2 Sequence Assemblages among Coral Colonies

Endosymbiotic dinoflagellates in the genus Symbiodinium are fundamentally important to the biology of scleractinian corals, as well as to a variety of other marine organisms. The genus Symbiodinium is genetically and functionally diverse and the taxonomic nature of the union between Symbiodinium and corals is implicated as a key trait determining the environmental tolerance of the symbiosis. Surprisingly, the question of how Symbiodinium diversity partitions within a species across spatial scales of meters to kilometers has received little attention, but is important to understanding the intrinsic biological scope of a given coral population and adaptations to the local environment. Here we address this gap by describing the Symbiodinium ITS2 sequence assemblages recovered from colonies of the reef building coral Montipora capitata sampled across Kāne'ohe Bay, Hawai'i. A total of 52 corals were sampled in a nested design of Coral Colony(Site(Region)) reflecting spatial scales of meters to kilometers. A diversity of Symbiodinium ITS2 sequences was recovered with the majority of variance partitioning at the level of the Coral Colony. To confirm this result, the Symbiodinium ITS2 sequence diversity in six M. capitata colonies were analyzed in much greater depth with 35 to 55 clones per colony. The ITS2 sequences and quantitative composition recovered from these colonies varied significantly, indicating that each coral hosted a different assemblage of Symbiodinium. The diversity of Symbiodinium ITS2 sequence assemblages retrieved from individual colonies of M. capitata here highlights the problems inherent in interpreting multi-copy and intra-genomically variable molecular markers, and serves as a context for discussing the utility and biological relevance of assigning species names based on Symbiodinium ITS2 genotyping

Global protected area expansion is compromised by projected land-use and parochialism

Peer reviewe

A Reckless Guide to P-values : Local Evidence, Global Errors.

This chapter demystifies P-values, hypothesis tests and significance tests and introduces the concepts of local evidence and global error rates. The local evidence is embodied in this data and concerns the hypotheses of interest for this experiment, whereas the global error rate is a property of the statistical analysis and sampling procedure. It is shown using simple examples that local evidence and global error rates can be, and should be, considered together when making inferences. Power analysis for experimental design for hypothesis testing is explained, along with the more locally focussed expected P-values. Issues relating to multiple testing, HARKing and P-hacking are explained, and it is shown that, in many situations, their effects on local evidence and global error rates are in conflict, a conflict that can always be overcome by a fresh dataset from replication of key experiments. Statistics is complicated, and so is science. There is no singular right way to do either, and universally acceptable compromises may not exist. Statistics offers a wide array of tools for assisting with scientific inference by calibrating uncertainty, but statistical inference is not a substitute for scientific inference. P-values are useful indices of evidence and deserve their place in the statistical toolbox of basic pharmacologists