For example, many national health and economic surveys are carried out by federal statistical agencies using complex designs. Also, many surveys of animal and human populations that academic researchers collect themselves involve complex sampling designs. This newsletter describes what features make a survey complex. The purpose of sampling in surveys is to take measurements on a representative portion of the population so that the whole population does not have to be measured. In a simple survey, each observation in the sample represents the same number of population members.
Complex surveys differ from simple surveys in two fundamental ways.
First, a complex survey samples observations within strata, typically with disproportionate sampling probabilities. The population is divided into sub-populations, i.e., strata, and observations are sampled from within each stratum. For example, in many national surveys, strata are defined based upon geographic region. Observations sampled from one stratum may represent more or less population members than observations sampled from another stratum. That is, the sampling proportions across strata differ.