# statsmodels.stats.contingency_tables.Table.test_ordinal_association¶

Table.test_ordinal_association(row_scores=None, col_scores=None)[source]

Assess independence between two ordinal variables.

This is the ‘linear by linear’ association test, which uses weights or scores to target the test to have more power against ordered alternatives.

Parameters: row_scores (array-like) – An array of numeric row scores col_scores (array-like) – An array of numeric column scores A bunch with the following attributes statistic (float) – The test statistic. null_mean (float) – The expected value of the test statistic under the null hypothesis. null_sd (float) – The standard deviation of the test statistic under the null hypothesis. zscore (float) – The Z-score for the test statistic. pvalue (float) – The p-value for the test.

Notes

The scores define the trend to which the test is most sensitive.

Using the default row and column scores gives the Cochran-Armitage trend test.