An evaluation of three statistics of structured exploratory data analysis

The power of structured exploratory data analysis (SEDA) to discriminate among major genic, polygenic, and nongenetic determination of phenotypes was investigated using computer simulation. Three classes of SEDA indices (the major gene index, the offspring between parents function, and the midparent-child correlation coefficient) were evaluated. These three statistics, in combination, were reasonably sensitive in detecting the presence of a major locus and in discriminating between phenotypes with genetic effects and those with no genetic component. However, they were unable to discriminate between major genic and polygenically determined phenotypic models.