One-way between-subjects ANOVA Flashcards
assumptions
DV is interval or ratio level data
Data is normally distributed (histogram)
Homogeneity of variance (same variance)
Independent-random samples taken from each population
SPSS outputs
between subjects factors
descriptives table
levenes test for equality of error variances
tests of between-subjects effects
profile plots
between subjects factors
identify levels of factors and number of ppts
descriptives table
mean and SD to report results
shows where differences occur if significant result
levenes test for equality of error variances
use based on mean
want a non-significant value (p>0.05)
suggests variances aren’t significantly different
tests of between-subjects effects
shows DF, mean square, F at significant level
reporting the ANOVA (main effect) results
(what do we use?)
use tests of between subjects effects table
F( , )= . ,p<.001
effect size calculation
sum of squares for BG condition (hypothesis)/total sum of squares (hypothesis+error)
partial eta square
eta square
Cohen 1988 guidelines
effect sizes
small = 0.01
medium = 0.059
large = 0.138
steps for formally reporting ANOVA
- State ANOVA type, effect of DV
- Present means and SD in table or text
- Mention assumptions
- Report ANOVA results (F ratio)
- Report effect sizes and meaning
- Report comparisons
Next steps after the anova
planned/unplanned comparisons
when to use planned comparisons for one way between subjects anova
when no significant main effect
used when hypothesised difference made in advance is explored
planned comparisons for one way between subjects anova
Contrasts tests table (assumes equal variances line)
Contrasts effects sizes table (point estimate is effect size)
- Find both the above for each comparison
Report analysis resultsInterpret results
reporting results of planned comparisons for one way between subjects anova
- Planned comparisons were performed to test hypotheses.
- See table 1 to see means and SD for each groups DV (draw table)
- Comment on means for DV and whether they were significantly higher or lower in each condition.
- t( )= . ,p<.001
- state effect and size
interpret in words
when to use unplanned comparisons for one way between subjects anova
used if no hypothesised difference is explained
main effect needs to be significant to be run