The definition of phenotype is a major problem in genetic studies of psychiatric disorders. Most linkage studies in bipolar disorder have defined the phenotype as a dichotomous trait and have usually employed different hierarchical classifications in order to overcome uncertainty resulting from phenotypic variability. In this study we explored the advantages of maximizing the evidence for linkage over different phenotypic definitions when conducting parametric linkage analysis of a complex trait. The GAW10 Problem 1 was used, focusing on chromosome 18 data sets. Three major phenotypic models were analyzed: quasi-quantitative, liability-based and affection-status models. Overall, no single phenotypic model performed consistently better than the others (i.e., lod scores greater than 1.0). Each model yielded higher lod scores than the others in particular instances, suggesting that it might be useful in exploratory data analysis, where the phenotype is variable, to maximize evidence for linkage over different phenotypic models.