My goal in this post wasn't to explain the causes of the phenomenon, but, yes, that is one potential hypothesis of the cause of the greater male variability. At this point, I'm not confident in what the true explanation is. That hypothesis would explain greater male variability, but I'm not sure if it would help explain the positive relationship between mean effect size and variance ratio.
My goal in this post wasn't to explain the causes of the phenomenon, but, yes, that is one potential hypothesis of the cause of the greater male variability. At this point, I'm not confident in what the true explanation is. That hypothesis would explain greater male variability, but I'm not sure if it would help explain the positive relationship between mean effect size and variance ratio.
yeah, if you assume a model where the female has 5% of her genome mixed due to inactivation, uniformly distributed effect sizes across the genome for a quantitative trait, and male variance = sigma ^ 2, I think you'd get
VR0 = sigma ^ 2 / ((((.95 ^ 2) * sigma ^ 2) + ((.05 ^ 2) * (sigma ^ 2 / 4))) = 1.11, which isn't too much different than you'd suggest.
My goal in this post wasn't to explain the causes of the phenomenon, but, yes, that is one potential hypothesis of the cause of the greater male variability. At this point, I'm not confident in what the true explanation is. That hypothesis would explain greater male variability, but I'm not sure if it would help explain the positive relationship between mean effect size and variance ratio.
yeah, if you assume a model where the female has 5% of her genome mixed due to inactivation, uniformly distributed effect sizes across the genome for a quantitative trait, and male variance = sigma ^ 2, I think you'd get
VR0 = sigma ^ 2 / ((((.95 ^ 2) * sigma ^ 2) + ((.05 ^ 2) * (sigma ^ 2 / 4))) = 1.11, which isn't too much different than you'd suggest.