014: On the "Probable Error" of a Coefficient of Correlation Deduced from a Small Sample.

By R. Fisher

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In Statistics and Probability

Citations in the corpus

Conditioning, Likelihood, and Coherence: A Review of Some Foundational Concepts (2000, background): “Fisher (1921, 1925, 1934) defined the likelihood function as i= I Of course, the likelihood function appeared implicitly much earlier in the work of Bayes and Laplace, who used what we now call Bayesian inference to solve statistical problems.”
Measuring functional connectivity during distinct stages of a cognitive task (2004, methodology): “To allow statistical conclusions to be made based on the correlation magnitudes, we applied an arc-hyperbolic tangent transform (Fisher, 1921) to the correlation coefficients of all brain voxels.”
A NIRS-fMRI investigation of prefrontal cortex activity during a working memory task (2013, unknown): “(4))(Fisher, 1915, 1921): Z ¼ 1 2 ln 1þ r 1−r : ð4Þ The correlation Z-values were tested using a one-sample t test against zero.”
Asiya: An Open Toolkit for Automatic Machine Translation (Meta-)Evaluation (2010, methodology): “Since the sampling distribution of correlation coefficients is not normally distributed, they are first converted to Fisher’s z using the Fisher transformation (Fisher, 1921).”
Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics (2001, unknown): “One possible way of improving the finite sample behaviour of the asymptotic distribution of ρ̂i(12) is by using the Fisher (1921)-z transformation (e.g. see the exposition in Anderson (1984, 122-124)) zi(12) = 1 2 log 1 + ρ̂i(12) 1 − ρ̂i(12) and ζi(12) = 1 2 log 1 + ρi(12) 1 − ρi(12) .”
The estimation of R 2 and adjusted R 2 in incomplete data sets using multiple imputation (2009, methodology): “In order to transform this type of data, one can use the Fisher z transformation [11] which was developed to deal with proportions.”
Eigengene networks for studying the relationships between co-expression modules (2007, background): “Many statistical tests have been proposed to test for differences between correlations, e.g. , [14-16].”
Geometric Interpretation of Gene Coexpression Network Analysis (2008, methodology): “Thus, one can use a correlation test p-value [53] or a regression-based p-value for assessing the statistical significance between E and the sample trait T.”
A spreadsheet for deriving a confidence interval, mechanistic inference and clinical inference from a P value (2007, methodology): “The Fisher (1921) z transformation is used for correlations, and a sample size rather than a p value is required.”
IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes (2018, methodology): “New tools are intended to cover all major scenarios of statistical analysis and are based on five statistical methods: Fisher’s Exact (30), Mann–Whitney (31) and Welch’s T-test (32) are used to compare two groups or sets of genomes, while Analysis of Variance or ANOVA (33) and Kruskal–Wallis (34) ar”
Factors Affecting Higher Order Thinking Skills of Students: A Meta-Analytic Structural Equation Modeling Study. (2015, methodology): “(Fisher, 1921; Hedges and Olkin's, 1985) 1.2) Next, we tested the homogeneity of correlations from 1.1.”