ASSESSING THE STATISTICAL POWER TO DETECT LINKAGE IN A SAMPLE OF 51 BIPOLAR AFFECTIVE-DISORDER PEDIGREES

We used computer simulation method to address the question of power in an initial collaborative sample of 51 bipolar affective disorder pedi grees. Simulations were performed for all possible combinations using (1) two levels of diagnostic stringency, (2) three transmission models , (3) locus heterogeneity, and (4) different assumed phenocopy rates. Some of the factors that affect the Fewer to detect linkage are (1) th e specification of the correct genetic model, (2) the degree of locus heterogeneity, and (3) the frequency of phenocopies. The first two ass ertions were supported by our simulation results, but varying the rate s of phenocopy did not substantially alter the power of the sample unt il a critical point. However, it is important to point out that these results are dependent on the genetic models under study and on the use of the ''correct'' model (i.e., the one used to simulate the data). I f we assume a dominant mode of inheritance and locus homogeneity, the power to detect linkage is 97.5% at a theta of .01. However, the power declines dramatically, to 60.5 and 14.7%, if only 75 and 50% of the f amilies are linked, respectively. Locus heterogeneity has a similar ef fect on the power of the sample to exclude linkage. The relative lack of power in our data, in the presence of significant locus heterogenei ty, and for an intermediate mode of inheritance, underscores the need for multicenter collaboration.