Genotypic correlation and regression in social groups: multiple alleles, multiple loci and subdivided populations.

Genotypic correlations and regressions can be estimated from multiallelic data sets either by weighting the allelic effects additively or by specifically weighting the genotypic interactions. Both methods can be extended to multiple loci, but they do not fully take into account the joint segregation patterns at the loci. These genotypic statistics have a great importance in sociobiological contexts, as they can be used for genetic descriptions of social structures. In this paper I examine the two estimation methods and show how the genotypic correlation and regression coefficients from genotypic interactions are connected to other statistics of standard population genetics; special emphasis is given to the sample-size correction when intracolony correlations from small samples were estimated. I also show how genotypic correlation and regression can be estimated in subdivided populations, both in continuous populations with isolation by distance and in populations divided into separate subpopulations. The latter analysis is an example of a more general hierarchic correlation analysis.