Southwest Respiratory and Critical Care Chronicles, 2014 Shengping Yang, Gilbert Berdine
doaj +5 more sources
Parametric and Nonparametric Tests in Spine Research: Why Do They Matter? [PDF]
Global Spine J, 2018 Parametric and nonparametric are 2 broad classifications of statistical procedures. Parametric tests are based on assumptions about the distribution of the underlying population from which the sample was taken.
Hopkins S, Dettori JR, Chapman JR.
europepmc +2 more sources
Effect sizes for nonparametric tests. [PDF]
Biochem Med (Zagreb)Effect size measures are important complements to P values, providing information about the magnitude and practical relevance of research findings. While widely discussed in the context of parametric tests, effect size estimation for nonparametric tests ...
Fiel Peres F.
europepmc +2 more sources
The aggregation paradox for statistical rankings and nonparametric tests. [PDF]
PLoS ONE, 2020 The relationship between social choice aggregation rules and non-parametric statistical tests has been established for several cases. An outstanding, general question at this intersection is whether there exists a non-parametric test that is consistent ...
Haikady N Nagaraja, Shane Sanders
doaj +2 more sources
Nonparametric statistical tests for the continuous data: the basic concept and the practical use [PDF]
Korean Journal of Anesthesiology, 2016 Conventional statistical tests are usually called parametric tests. Parametric tests are used more frequently than nonparametric tests in many medical articles, because most of the medical researchers are familiar with and the statistical software ...
Francis Sahngun Nahm
doaj +2 more sources
Nonparametric Tests for Differential Histone Enrichment with ChIP-Seq Data [PDF]
Cancer Informatics, 2015 Chromatin immunoprecipitation sequencing (ChIP-seq) is a powerful method for analyzing protein interactions with DNA. It can be applied to identify the binding sites of transcription factors (TFs) and genomic landscape of histone modification marks (HMs).
Qian Wu, Kyoung-Jae Won, Hongzhe Li
doaj +3 more sources
Robust multivariate nonparametric tests for detection of two-sample location shift in clinical trials. [PDF]
PLoS ONE, 2018 This article presents and investigates performance of a series of robust multivariate nonparametric tests for detection of location shift between two multivariate samples in randomized controlled trials.
Xuejun Jiang +4 more
doaj +2 more sources
Nonparametric Tests for Exponentiality Against IFRA Alternatives Based on Cumulative Extropy Measures [PDF]
EntropyThis paper develops two nonparametric test statistics for testing exponentiality against alternatives in the increasing failure rate average (IFRA) class.
Anfal A. Alqefari
doaj +2 more sources
Deciphering the dilemma of parametric and nonparametric tests
Journal of the Practice of Cardiovascular Sciences, 2016 The potential source of complexity while analyzing the data is to choose on whether the data collected could be analyzed properly by the application of parametric tests or nonparametric tests.
Rakesh Kumar Rana +2 more
doaj +2 more sources
On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests [PDF]
Entropy, 2017 Nonparametric two-sample or homogeneity testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. The literature is old and rich,
Aaditya Ramdas +2 more
doaj +2 more sources