Robustness and power of the unified model in the analysis of quantitative measurements

Abstract

The resolution between skewness in the distribution of a quantitative trait and segregation of a major gene is a difficult issue in family studies. Quantitative data were simulated on six-member nuclear families in order to study the behavior of the unified model under these circumstances. Replicates of 100 nuclear families were generated assuming a multifactorial model with skewness. In the range where a major gene was falsely detected in 80%-100% of the simulations analyzed under the transmission probability or mixed models, use of the unified model reduces the frequency of false inference to between 10% and 40%. This protection against a false conclusion requires estimation of the three transmission probabilities and testing hypotheses of Mendelian transmission and equal transmission probabilities. Alternatively, it was shown that use of a transformation to remove skewness induced by a major gene leads to a decrease of power of approximately 55%. These results suggest that the unified model may obviate the need to compare analyses performed on transformed and untransformed data, particularly when skewness is low (less than 0.2) or high (greater than 0.4). For intermediate skewness (0.2-0.4), estimating segregation parameters under the mixed model simultaneously with a transformation to remove residual skewness can be considered as an alternative method.