ANOVA - injury
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95% CI for ω²ₚ | |||||||||||||||||
Cases | Sum of Squares | df | Mean Square | F | p | ω²ₚ | Lower | Upper | |||||||||
athlete | 99.008 | 1 | 99.008 | 64.822 | < .001 | 0.347 | 0.213 | 0.467 | |||||||||
stretch | 16.875 | 1 | 16.875 | 11.048 | 0.001 | 0.077 | 0.010 | 0.186 | |||||||||
switch | 85.008 | 1 | 85.008 | 55.656 | < .001 | 0.313 | 0.180 | 0.436 | |||||||||
athlete ✻ stretch | 1.875 | 1 | 1.875 | 1.228 | 0.270 | 0.002 | 0.000 | 0.048 | |||||||||
athlete ✻ switch | 69.008 | 1 | 69.008 | 45.181 | < .001 | 0.269 | 0.140 | 0.394 | |||||||||
stretch ✻ switch | 21.675 | 1 | 21.675 | 14.191 | < .001 | 0.099 | 0.019 | 0.214 | |||||||||
athlete ✻ stretch ✻ switch | 9.075 | 1 | 9.075 | 5.942 | 0.016 | 0.040 | 0.000 | 0.132 | |||||||||
Residuals | 171.067 | 112 | 1.527 | ||||||||||||||
Note. Type III Sum of Squares |
There was a significant athlete by stretch by switch interaction *F*(1, 112) = 5.94, *p* < .05,
As you can see below, a three-way interaction effect implies that a two-way interaction is influenced by a third variable. You can shuffle around the variables and the boxes they are assigned to, to get a clear idea of how the three-way interaction is manifested in the data.
Simple Main Effects - stretch
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Level of athlete | Level of switch | Sum of Squares | df | Mean Square | F | p | |||||||
Athlete | Playing switch | 4.800 | 1 | 4.800 | 3.143 | 0.079 | |||||||
Watching switch | 0.300 | 1 | 0.300 | 0.196 | 0.658 | ||||||||
Non-athlete | Playing switch | 43.200 | 1 | 43.200 | 28.284 | < .001 | |||||||
Watching switch | 1.200 | 1 | 1.200 | 0.786 | 0.377 | ||||||||