Social and economic data commonly have a nested
structure (for example, households nested within neighborhoods). Recently
techniques and computer programs have become available for dealing with such
data, permitting the formulation of explicit multilevel models with
hypotheses about effects occurring at each level and across levels. If data
users are planning to analyze survey data using multilevel models rather
than concentrating on means, totals, and proportions, this needs to be
accounted for in the survey design. The implications for determining sample
sizes (for example, the number of neighborhoods in the sample and the number
of households sampled within each neighborhood) are explored.