Archive:Advanced ANOVA/Assumptions: Difference between revisions
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==[[Research methods and professional ethics/ANOVA| | This page outlines and summarises the assumptions for various ANOVA models. | ||
==All models== | |||
# [[Dependent variable]]s must be: | |||
#* Measured at interval or ratio level [[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) | |||
==[[Research methods and professional ethics/Testing differences|''t''-tests]], [[Research methods and professional ethics/ANOVA|one-way ANOVA]] and [[Research methods and professional ethics/Factorial ANOVA|factorial ANOVA]]== | |||
# The data in each cell is '''[[normality|normally distributed]]'''. | # The data in each cell is '''[[normality|normally distributed]]'''. | ||
# '''Homogeneity of variance''' | # '''Homogeneity of variance''': | ||
# '''Cells are independent''' (the scores in one cell are not dependent on the scores in another cell). | #* 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. | |||
<noinclude>[[Category:Research methods and professional ethics]]</noinclude> | <noinclude>[[Category:Research methods and professional ethics]]</noinclude> | ||
Revision as of 03:34, 18 August 2008
This page outlines and summarises the assumptions for various ANOVA models.
All models
- Dependent variables must be:
- Measured at interval or ratio level 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:
- 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.