ROBUSTNESS AND POWER OF THE UNIFIED MODEL IN THE ANALYSIS OF QUANTITATIVE MEASUREMENTS

  • 1 February 1986
    • journal article
    • research article
    • Vol. 38  (2) , 228-234
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 behaviour 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 probabilites. 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 (< 0.2) or high (> 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.