Word Doc Week 7 Flashcards
ANOVA
One-way (single-factor) Analysis of Variance
ANOVA can be used in a variety of ways
- Independent groups
- Repeated measures
- Matched samples
- Designs involving mixtures of independent groups and repeated measures
- More than one independent variable can be evaluated at the same time
- ANOVA can be tailored to address virtually any research question.
F statistic - Sources of Variability in a data set
Between-group variability
Within-group variability
Treatment+individual differences+experimental error
Individual differences+experimental error (error term)
- If there is no treatment effect at all, then F = 1
- the stronger the treatment the bigger value of F ration
- Does not have an upper limit
- Cannot be negative
Null Hypothesis for ANOVA
- Group 1 - MOL treatment
- Group 2 - Drug treatment
- Group 3 - Imagery treatment
- Group 4 - No treatment Control Grou
Post-Hoc Tests
- Tests carried out after you have obtained a significant overall ANOVA
- Locates the sources of significance in the F ratio
- Overall F must be significant to justify the use of post-hoc tests
Types of Post-Hoc tests
- Scheffé test
- Newman-Keuls test
- Tukey’s Honestly Significant Different Test
- Fisher’s Least Significant Different Test
These tests do the same thing, tests every group with every group to unpack a significant result
Pairwise Comparisons
Is there a significant difference between each pair of group means
Planned Comparisons - Priori Tests
- Specific hypothesis involve sub-groups of you experiment
- Carried out instead of overall ANOVA followed by post-hoc tests
- can test complex comparisons that involve combinations of groups
Advantages of Planned Comparisons over Post-Hoc tests
- More likely to find a significant difference with a planned comparison than with an equivalent post-hoc test
- Are statistically more powerful.
- Can design complex comparisons
Advantages of Post-Hoc tests over Planned Comparisons
- can compare each group with each group
- planned comparisons permit a smaller number of focussed comparisons
Rules for Planned Comparisons
- Done instead of an overall ANOVA
- Maximum number of planned comparisons you can have is the number of groups
- Your contrast coefficients must sum to zero
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