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Wilcoxon signed-rank test

 
Statistics Dictionary: Wilcoxon signed-rank tests

Non-parametric tests that extend the sign tests. The single-sample version (observations x1, x2,...), suitable for a symmetric distribution, tests the null hypothesis that the population median has a specified value (m0). The matched-pair (or paired-sample) version (observation pairs (x1, y1), (x2, y2),...) is concerned with the differences (x1y1), (x2y2),.... With the assumption that these differences are independent observations from a symmetric distribution, the null hypothesis is that this distribution has median zero.

To determine the value of the test statistic, z, the first step is to calculate the differences d1, d2, ..., where dj=xjm0 (single sample) or dj=xjyj (matched pairs). After zero differences have been discarded, the remaining n are arranged in ascending order of |dj|. The magnitudes are replaced by the corresponding ranks, with tied ranks where necessary. The signs of d1, d2,..., are now attributed to the ranks, resulting in signed ranks. Let P be the sum of the positive signed ranks and let T be the smaller of P and ½n(n+1)-P. The test statistic, given by




is an observation from the upper half of an approximate standard normal distribution. The ½ is a continuity correction.

As an example, suppose that a symmetric distribution is believed to have median 100. A random sample of eight observations is reported as consisting of the values 92.3, 57.6, 88.8, 110.5, 100.0, 181.0, 96.0, 105.7. The supposed median is subtracted from each observation to give −7.7, −42.4, −11.2, 10.5, 0, 81.0, −4.0, 5.7. The value 0 is discarded and the remainder are arranged in order of ascending absolute magnitude: −4.0, 5.7, −7.7, 10.5, −11.2, −42.4, 81.0. Retaining the signs while replacing the values by ranks gives −1, 2, −3, 4, −5, −6, 7, so that p = 13, ½n(n+1) − P=15 (since n=7) and T=13. The test statistic is





Comparing with the tables of upper-tail percentage points of the standard normal distribution (Appendix VI), we see that the null hypothesis that the median is 100 should not be rejected.



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Wikipedia: Wilcoxon signed-rank test
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The Wilcoxon signed-rank test is a non-parametric statistical hypothesis test for the case of two related samples or repeated measurements on a single sample. It can be used as an alternative to the paired Student's t-test when the population cannot be assumed to be normally distributed. The test is named for Frank Wilcoxon (1892–1965) who, in a single paper, proposed both it and the rank-sum test for two independent samples (Wilcoxon, 1945).

Like the t-test, the Wilcoxon test involves comparisons of differences between measurements, so it requires that the data are measured at an interval level of measurement. However it does not require assumptions about the form of the distribution of the measurements. It should therefore be used whenever the distributional assumptions that underlie the t-test cannot be satisfied.

Contents

Setup

Suppose we collect 2n observations, two observations of each of the n subjects. Let i denote the particular subject that is being referred to and the first observation measured on subject i be denoted by xi and second observation be yi.

Assumptions

  1. Let Zi = Yi – Xi for i = 1, ... , n. The differences Zi are assumed to be independent.
  2. Each Zi comes from a continuous population (they must be identical) and is symmetric about a common median θ.

Test procedure

The null hypothesis tested is H0: θ = 0. The Wilcoxon signed rank statistic W+ is computed by ordering the absolute values |Z1|, ..., |Zn|, the rank of each ordered |Zi| is given a rank of Ri. Denote the positive Zi values with φi = I(Zi > 0), where I(.) is an indicator function. The Wilcoxon signed ranked statistic W+ is defined as

W_+ = \sum_{i=1}^n \varphi_i R_i.\,\!

It is often used to test the difference between scores of data collected before and after an experimental manipulation, in which case the central point under the null hypothesis would be expected to be zero. Scores exactly equal to the central point are excluded and the absolute values of the deviations from the central point of the remaining scores is ranked such that the smallest deviation has a rank of 1. Tied scores are assigned a mean rank. The sums for the ranks of scores with positive and negative deviations from the central point are then calculated separately. A value S is defined as the smaller of these two rank sums. S is then compared to a table of all possible distributions of ranks to calculate p, the statistical probability of attaining S from a population of scores that is symmetrically distributed around the central point.

As the number of scores used, n, increases, the distribution of all possible ranks S tends towards the normal distribution. So although for n ≤ 20, exact probabilities would usually be calculated, for n > 20, the normal approximation is used. The recommended cutoff varies from textbook to textbook — here we use 20 although some put it lower (10) or higher (25).

The Wilcoxon test was popularised by Siegel (1956) in his influential text book on non-parametric statistics. Siegel used the symbol T for the value defined here as S. In consequence, the test is sometimes referred to as the Wilcoxon T test, and the test statistic is reported as a value of T.

See also

References

  • Corder, G.W. & Foreman, D.I. (2009) Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach, New Jersey: Wiley.
  • Siegel, S. (1956). Non-parametric statistics for the behavioral sciences, 75-83 New York: McGraw-Hill.
  • Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometrics, 1, 80-83.

External links

Implementations

  • ALGLIB includes implementation of the Wilcoxon signed-rank test in C++, C#, Delphi, Visual Basic, etc.
  • The free statistical software R includes an implementation of the test as wilcox.test(x,y, paired=TRUE), where x and y are vectors of equal length.

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Statistics Dictionary. A Dictionary of Statistics. Second edition revised. Copyright © Oxford University Press, 2008. All rights reserved.  Read more
Wikipedia. This article is licensed under the Creative Commons Attribution/Share-Alike License. It uses material from the Wikipedia article "Wilcoxon signed-rank test" Read more