How should one interpret heritability? Is it related to $R^2$?
From Wikipedia:
Heritability estimates are often misinterpreted if it is not understood that they refer to the proportion of variation between individuals on a trait that is due to genetic factors. It does not indicate the degree of genetic influence on the development of a trait of an individual. For example, it is incorrect to say that since the heritability of personality traits is about .6, that means that 60% of your personality is inherited from your parents and 40% comes from the environment.
So what is the plain english interpretation of heritability?
Is it supposed to be the genetics version of $R^2$? If so, please explain it to me anyway because I forgot my statistics.
I found this so from what I understand, one might say:
If height is estimated to be 80% heritable, and if we get 10 people, get their heights and then compute the variance, we say that around 80% of that variance is likely due to genetic factors while the remaining 20% is due to other things.
Such interpretation of heritability seems to work for non-categorical traits. What about categorical or binary traits?
Hair and eye colour is categorical (I think?). 882
So what, we assign a number for each colour and then compute the variance?
ADHD is binary (I think?). Do we assign 0 for not having and 1 for having then compute variance?
I seem to recall regressing binary or categorical variables needs some kind of adjustments and hence interpretations of estimates (such as intercepts or slopes) may be different.
Also, the book linked above says
heritability represents the degree to which the variance in a trait is attributable to genetics in the population on average
Combining that with the Wiki paragraph above, I don't think someone saying
Eye colour is around 98% heritable. I have brown eyes. Therefore, around 98% of the reason why I have brown eyes is genetics.
is far off from saying
If we have a million people who near-identically flip a million near-identical coins a hundred times, and we compute the average of the coin flips that turn out to be heads to be 58.6, then the probability that you will flip heads when you near-identically flip this near-identical coin is around 58.6%.
Is it? (Of course 'near', 'around', etc are not always used similarly...lol)
So yeah, technically the 60/40 interpretation in the Wiki example is technically wrong but practically it's around 60% $\pm$ some standard deviation? 655