Archive:Advanced ANOVA/Assumptions: Difference between revisions

Revision as of 01:26, 5 December 2008

Template:50%done This page outlines the assumptions for various ANOVA models, including t-tests.

Dependent variables must be:
- Measured at interval or ratio level of measurement.
- Normally distributed in all groups of the independent variable.
  - ANOVA is quite robust to violations of this assumption if sample sizes are large and approximately equal (> 15 cases per group)

The data in each cell is normally distributed.
Homogeneity of variance:
- The variance for each cell should be similar - a rule of thumb is that one SD should not be more than double another cell SD.
- If violated,
  - the p-values for significance tests are inaccurate.
  - SPSS has post-hoc tests to adjust for this.
Cells are independent - Cases represent random samples from the target populations and the scores of the test variable should be independent of each other (i.e., the scores in one cell are not dependent on the scores in another cell).
- Inaccurate p-values are produced if the independence assumption is violated.

@@ Line 4: / Line 4: @@
 ==All models==
 # [[Dependent variable]]s must be:
-#* Measured at interval or ratio level [[level of measurement]].
+#* Measured at interval or ratio [[level of measurement]].
 #* [[Normal distribution|Normally distributed]] in all groups of the [[independent variable]].
 #** ANOVA is quite robust to violations of this assumption if sample sizes are large and approximately equal (> 15 cases per group)