Chi-square tests
Chi-square tests of homogeneity and independence.
Computes the P-value for I x J - table row/col independence.
Ref.: DeltaProt toolbox at http://services.cbu.uib.no/software/deltaprot/
Input:
X: data matrix (I x J -table) of the observed frequency cells.
method: 'RC': Read-Cressie power divergence statistics (default), lambda= 2/3
'Pe': Standard Pearson chi2-distance, lambda= 1
'LL': Log Likelihood ratio distance, lambda= 0
Output:
P-value
Use: P = chi2Tests(Observed,'RC')
The P-value is computed through approximation with chi-2 distribution
under the null hypothesis for all methods.
The 'RC'-method is sligtly better than the 'Pe'-method in small tables with unbalanced column margins
Please, use the following reference:
Thorvaldsen, S. , Flå, T. and Willassen, N.P. (2010) DeltaProt: a software toolbox for comparative genomics. BMC Bioinformatics 2010, Vol 11:573.
See http://www.biomedcentral.com/1471-2105/11/573
Other reference:
Rudas, T. (1986): A Monte Carlo Comparision of Small Sample Behaviour
of The Pearson, the Likelihood Ratio and the Cressie-Read Statistics. J.Statist. Comput. Simul, vol 24, pp 107-120.
Read, TRC and Cressie, NAC (1988): Goodness of Fit Statistics for Discrete Multivariate Data. Springer Verlag.
Ewens, WJ and Grant, GR (2001): Statistical Methods in Bioinformatics. Springer Verlag.
Cite As
Steinar Thorvaldsen (2024). Chi-square tests (https://www.mathworks.com/matlabcentral/fileexchange/29817-chi-square-tests), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.