Fourteen Homogeneity of Variance Tests: When and How To Use Them.

Homogeneity of variance (HOV) is a major assumption underlying the validity of many parametric tests. More importantly, it serves as the null hypothesis in substantive studies that focus on cross- or within-group dispersion. Despite a widely acknowledged need for testing HOV, very few textbooks give adequate coverage on the topic, and many HOV tests are still missing from statistical software packages. Using language comprehensible to those who have completed only 1 introductory statistics course in college, this paper explains 14 representative HOV tests for 5 types of research situations: (1) 1-sample HOV test; (2) 2-sample HOV test; (3) HOV test involving 2 or more samples; (4) HOV test for factorial designs; and (5) HOV tests for 2 correlated samples. Brief guidelines are provided as to when and how each of the HOV tests is to be used, and sample programs are included for HOV tests available from the SAS/STAT system. All the remaining tests can be very easily calculated by hand using descriptive statistics. The paper concludes with a conceptual summary of four major approaches to HOV testing. (Contains 19 references.) (SLD)