Publication date: 04/12/2021

You can test for homogeneity of variation within groups using the following options:

• ANOM for Variances

• ANOM for Variances with Levene (ADM)

• ANOM for Ranges

Use this method to compare group standard deviations (or variances) to the root mean square error (or mean square error). This method assumes that your data is approximately normally distributed. To use this method, each group must have at least four observations. For more information about the ANOM for Variances test, see Wludyka and Nelson (1997) and Nelson et al. (2005). For an example, see Example of an Analysis of Means for Variances Chart.

This method provides a robust test that compares the group means of the absolute deviations from the median (ADM) to the overall mean ADM. Use ANOM for Variances with Levene (ADM) if you suspect that your data is non-normal and cannot be transformed to normality. ANOM for Variances with Levene (ADM) is a nonparametric analog of the ANOM for Variances analysis. For more information about the ANOM for Variances with Levene (ADM) test, see Levene (1960) or Brown and Forsythe (1974).

Use this test to compare group ranges to the mean of the group ranges. This is a test for scale differences based on the range as the measure of spread. See Wheeler (2003).

Note: ANOM for Ranges is available only for balanced designs and specific group sizes. See Restrictions for ANOM for Ranges Test.

Unlike the other ANOM decision limits, the decision limits for the ANOM for Ranges chart uses only tabled critical values. For this reason, ANOM for Ranges is available only for the following:

• groups of equal sizes

• groups specifically of the following sizes: 2–10, 12, 15, and 20

• number of groups between 2 and 30

• alpha levels of 0.10, 0.05, and 0.01

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).