25 June 2014
# gross association time
nigrensis$prefLargeMale <- nigrensis$timeLargeMale - nigrensis$timeSmallMale
# preference score
nigrensis$prefScore <- nigrensis$timeLargeMale / (nigrensis$timeLargeMale+nigrensis$timeSmallMale)
One thing we might want to know is whether there is a significant negative correlation between this ratio and female preference.
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.9041 0.09463 9.554 2.054e-17
nigrensis$maleToFemaleRatio -0.1856 0.07558 -2.455 1.514e-02
The residuals are ugly though, and log-transforming the ratio doesn't help:
Instead, we might want to do a a Spearman's rank corrlation test, which doesn't make any assumptions about the residuals.
Spearman's rank correlation rho
data: nigrensis$prefScore and nigrensis$maleToFemaleRatio
S = 936889, p-value = 0.0001114
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
-0.2981
This significant results holds whether we use preference score (shown in previous slide), or difference in association time.
cor.test(nigrensis$prefLargeMale,nigrensis$maleToFemaleRatio,method="spearman")
Spearman's rank correlation rho
data: nigrensis$prefLargeMale and nigrensis$maleToFemaleRatio
S = 901940, p-value = 0.001311
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
-0.2496
Next, I repeat all the analyses I did previous, but using the difference in number of glides a female displays towards the large and small males.
There are also no significant relationships between female size or the male:female size ratio and the number of glides.
For fun, I also wanted to see whether there was evidence that a female had a stronger preference towards the larger male when the ratio between the large and the small male was greater.