Newman–Keuls method
Encyclopedia
In statistics
, the Newman–Keuls method (named after D. Newman (1939), and M. Keuls (1952)) is a post-hoc test
used for comparisons after the performed F-test
(analysis of variance
) is found to be significant. The Newman–Keuls method is very similar to Tukey's HSD post-hoc test, except that it analyzes the differences in terms of layers.
For layer one, the test gives the same result as would be obtained using Tukey's HSD test. For layer two, use HSD,
instead of q(a, k, v), where k represents the number of group means being compared, q represents the according value from the studentized range, n is the number of groups, and v is the degrees of freedom
. (See mean squared error
.) Thus for layer three, we would have HSD, q(a, k − 2, v), and so on. Studentized range values can often be found from reference tables, and MS error is found from the original analysis of variance
results (ANOVA).
Statistics
Statistics is the study of the collection, organization, analysis, and interpretation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments....
, the Newman–Keuls method (named after D. Newman (1939), and M. Keuls (1952)) is a post-hoc test
Statistical hypothesis testing
A statistical hypothesis test is a method of making decisions using data, whether from a controlled experiment or an observational study . In statistics, a result is called statistically significant if it is unlikely to have occurred by chance alone, according to a pre-determined threshold...
used for comparisons after the performed F-test
F-test
An F-test is any statistical test in which the test statistic has an F-distribution under the null hypothesis.It is most often used when comparing statistical models that have been fit to a data set, in order to identify the model that best fits the population from which the data were sampled. ...
(analysis of variance
Analysis of variance
In statistics, analysis of variance is a collection of statistical models, and their associated procedures, in which the observed variance in a particular variable is partitioned into components attributable to different sources of variation...
) is found to be significant. The Newman–Keuls method is very similar to Tukey's HSD post-hoc test, except that it analyzes the differences in terms of layers.
For layer one, the test gives the same result as would be obtained using Tukey's HSD test. For layer two, use HSD,
instead of q(a, k, v), where k represents the number of group means being compared, q represents the according value from the studentized range, n is the number of groups, and v is the degrees of freedom
Degrees of freedom (statistics)
In statistics, the number of degrees of freedom is the number of values in the final calculation of a statistic that are free to vary.Estimates of statistical parameters can be based upon different amounts of information or data. The number of independent pieces of information that go into the...
. (See mean squared error
Mean squared error
In statistics, the mean squared error of an estimator is one of many ways to quantify the difference between values implied by a kernel density estimator and the true values of the quantity being estimated. MSE is a risk function, corresponding to the expected value of the squared error loss or...
.) Thus for layer three, we would have HSD, q(a, k − 2, v), and so on. Studentized range values can often be found from reference tables, and MS error is found from the original analysis of variance
Analysis of variance
In statistics, analysis of variance is a collection of statistical models, and their associated procedures, in which the observed variance in a particular variable is partitioned into components attributable to different sources of variation...
results (ANOVA).