Power to detect genetic and environmental influences increases not only with sample size but also with the number of measurements through longitudinal and/or multivariate designs, if those measurements correlate with each other. Power simulations are presented for uni- through quadrivariate cases, with differing genetic and environmental parameters. Even though subject attrition is a problem for most longitudinal studies, the gain in power available may more than make up for this shortcoming in many situations. In terms of planning studies to examine genetic and environmental influences, power calculations should not only consider sample size but number of measurements on particular phenotypes and their intercorrelations.