Results 241 to 250 of about 765,537 (296)

Comparative Evaluation of Smear Layer Removal by Various Endodontic Irrigating Solutions-An <i>In vitro</i> Study.

J Pharm Bioallied Sci
Palta S, Bhola M.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Privacy-preserving Kruskal–Wallis test

Computer Methods and Programs in Biomedicine, 2013
Statistical tests are powerful tools for data analysis. Kruskal-Wallis test is a non-parametric statistical test that evaluates whether two or more samples are drawn from the same distribution. It is commonly used in various areas. But sometimes, the use of the method is impeded by privacy issues raised in fields such as biomedical research and ...
Suxin Guo, Sheng Zhong, Aidong Zhang
exaly   +3 more sources

The Kruskal-Wallis Test and Stochastic Homogeneity

Journal of Educational and Behavioral Statistics, 1998
For the comparison of more than two independent samples the Kruskal-Wallis H test is a preferred procedure in many situations. However, the exact null and alternative hypotheses, as well as the assumptions of this test, do not seem to be very clear among behavioral scientists.
András Vargha, Harold D Delaney
exaly   +3 more sources

Kruskal–Wallis, Multiple Comparisons and Efron Dice

Australian and New Zealand Journal of Statistics, 2002
The Kruskal–Wallis test is a rank–based one way ANOVA. Its test statistic is shown here to be a quadratic form among the Mann–Whitney or Kendall tau concordance measures between pairs of treatments. But the full set of such concordance measures has more degrees of freedom than the Kruskal–Wallis test uses, and the independent surplus is attributable to
Brown, B. M., Hettmansperger, T. P.
exaly   +2 more sources

Estimation of the Power of the Kruskal‐Wallis Test

Biometrical Journal, 1996
AbstractPower calculations of a statistical test require that the underlying population distribution(s) be completely specified. Statisticians, in practice, may not have complete knowledge of the entire nature of the underlying distribution(s) and are at a loss for calculating the exact power of the test.
Mahoney, Michelle, Magel, Rhonda
openaire   +1 more source

Methodology and Application of the Kruskal-Wallis Test

Applied Mechanics and Materials, 2014
This paper describes the methodology and application of the very popular nonparametric test which is a rank based test named as Kruskal-Wallis. This test is useful as a general nonparametric test for comparing more than two independent samples. It can be used to test whether such samples come from the same distribution.
Eva Ostertagová, Oskar Ostertag, Jozef Kováč   +2 more
openaire   +1 more source

Combinatorics and Statistical Issues Related to the Kruskal–Wallis Statistic

Communications in Statistics - Simulation and Computation, 2014
We explore criteria that data must meet in order for the Kruskal–Wallis test to reject the null hypothesis by computing the number of unique ranked datasets in the balanced case where each of the m alternatives has n observations. We show that the Kruskal–Wallis test tends to be conservative in rejecting the null hypothesis, and we offer a correction ...
Anna E. Bargagliotti, Raymond N. Greenwell   +1 more
openaire   +1 more source

Unbiasedness and biasedness of the Jonckheere–Terpstra and the Kruskal–Wallis tests

Journal of the Korean Statistical Society, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Murakami, Hidetoshi, Lee, Seong Keon
openaire   +1 more source