Journal ArticleDOI
Effect size estimates: Current use, calculations, and interpretation.
TLDR
A straightforward guide to understanding, selecting, calculating, and interpreting effect sizes for many types of data and to methods for calculating effect size confidence intervals and power analysis is provided.Abstract:
The Publication Manual of the American Psychological Association (American Psychological Association, 2001, American Psychological Association, 2010) calls for the reporting of effect sizes and their confidence intervals. Estimates of effect size are useful for determining the practical or theoretical importance of an effect, the relative contributions of factors, and the power of an analysis. We surveyed articles published in 2009 and 2010 in the Journal of Experimental Psychology: General, noting the statistical analyses reported and the associated reporting of effect size estimates. Effect sizes were reported for fewer than half of the analyses; no article reported a confidence interval for an effect size. The most often reported analysis was analysis of variance, and almost half of these reports were not accompanied by effect sizes. Partial η2 was the most commonly reported effect size estimate for analysis of variance. For t tests, 2/3 of the articles did not report an associated effect size estimate; Cohen's d was the most often reported. We provide a straightforward guide to understanding, selecting, calculating, and interpreting effect sizes for many types of data and to methods for calculating effect size confidence intervals and power analysis.read more
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Journal ArticleDOI
Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients
Vancheswaran Gopalakrishnan,Vancheswaran Gopalakrishnan,Christine N. Spencer,Christine N. Spencer,Luigi Nezi,Alexandre Reuben,Miles C. Andrews,Tatiana Karpinets,Peter A. Prieto,D. Vicente,K. Hoffman,Spencer C. Wei,Alexandria P. Cogdill,Li Zhao,Courtney W. Hudgens,Diane S. Hutchinson,T. Manzo,M. Petaccia de Macedo,Tiziana Cotechini,T. Kumar,Wei Shen Chen,Sangeetha M. Reddy,R. Szczepaniak Sloane,Jessica Galloway-Peña,Hong Jiang,P. L. Chen,Elizabeth J. Shpall,Katayoun Rezvani,Amin M. Alousi,Roy F. Chemaly,Samuel A. Shelburne,Luis M Vence,Pablo C. Okhuysen,V. B. Jensen,Alton G. Swennes,Florencia McAllister,E. Marcelo Riquelme Sanchez,Yu Zhang,Laurence Zitvogel,Nicolas Pons,Jacob Austin-Breneman,Lauren E. Haydu,Elizabeth M. Burton,J. M. Gardner,E. Sirmans,Jing Shan Hu,Alexander J. Lazar,Takahiro Tsujikawa,Adi Diab,Hussein Abdul-Hassan Tawbi,Isabella C. Glitza,Wen-Jen Hwu,Sapna Pradyuman Patel,Scott E. Woodman,Rodabe N. Amaria,Michael A. Davies,Jeffrey E. Gershenwald,Patrick Hwu,J. E. Lee,Jianhua Zhang,Lisa M. Coussens,Zachary A. Cooper,P.A. Futreal,Carrie R. Daniel,Carrie R. Daniel,Nadim J. Ajami,Joseph F. Petrosino,Michael T. Tetzlaff,Pradeep Sharma,James P. Allison,Robert R. Jenq,Jennifer A. Wargo +71 more
TL;DR: Examination of the oral and gut microbiome of melanoma patients undergoing anti-programmed cell death 1 protein (PD-1) immunotherapy suggested enhanced systemic and antitumor immunity in responding patients with a favorable gut microbiome as well as in germ-free mice receiving fecal transplants from responding patients.
Journal ArticleDOI
The New Statistics Why and How
TL;DR: An eight-step new-statistics strategy for research with integrity is described, which starts with formulation of research questions in estimation terms, has no place for NHST, and is aimed at building a cumulative quantitative discipline.
Journal ArticleDOI
Bayesian Estimation Supersedes the t Test
TL;DR: Bayesian estimation for 2 groups provides complete distributions of credible values for the effect size, group means and their difference, standard deviations and their Difference, and the normality of the data.
Journal ArticleDOI
How Big Is “Big”? Interpreting Effect Sizes in L2 Research
Luke Plonsky,Frederick L. Oswald +1 more
TL;DR: This paper presented a description of L2 effects from 346 primary studies and 91 meta-analyses (N > 604,000) and found that Cohen's benchmarks generally underestimate the effects obtained in L2 research.
The need to report effect size estimates revisited. An overview of some recommended measures of effect size
Maciej Tomczak,Ewa Tomczak +1 more
TL;DR: In this article, the main objectives of this contribution are to promote various effect size measures in sport sciences through, once again, bringing to the readers' attention the benefits of reporting them, and to present examples of such estimates with a greater focus on those that can be calculated for non-parametric tests.
References
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Journal ArticleDOI
Sample Size Planning for Statistical Power and Accuracy in Parameter Estimation
TL;DR: In this paper, a review examines recent advances in sample size planning, not only from the perspective of an individual researcher, but also with regard to the goal of developing cumulative knowledge.
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Sample Size Planning for Statistical Power and Accuracy in Parameter Estimation
TL;DR: This review examines recent advances in sample size planning, not only from the perspective of an individual researcher, but also with regard to the goal of developing cumulative knowledge, for accuracy in parameter estimation (AIPE).
Journal ArticleDOI
Psychology Will Be a Much Better Science When We Change the Way We Analyze Data
TL;DR: For instance, this paper pointed out that the problem of replicating findings in psychology is a classic example of the "move on to the next one" problem. But this problem can also arise in other ways, e.g., in the regularity with which findings seem no t to replicate, or in the fact that one can find many hea r psychologists saying, " Well, this problem is solved now; let's move on to another" (e.g. Kepler must have said m ore than three centuries).
Journal ArticleDOI
When effect sizes disagree: the case of r and d.
TL;DR: The authors demonstrate the issue by focusing on two popular effect-size measures, the correlation coefficient and the standardized mean difference, both of which can be used when one variable is dichotomous and the other is quantitative.