We have discussed the role of survey weights and recognition of the sample structure in
developing both descriptive and analytic statistics from survey data. Survey data analysis
software that use survey weights and take account of the sample structure may be used to
estimate the parameters of both linear and logistic regression models based on survey data. The
estimates based on the sample are estimates of what would be obtained from fitting the models to
the entire finite population. Furthermore, standard errors of the estimates can also be obtained.
The explanatory variables in regression models applied to survey data are almost always
observed as they exist in the population rather than randomly assigned according to some
experimental design. Analysts need to be clear that regression coefficients based on survey data
simply reflect relationships that exist between the dependent variable and the explanatory
variables in the population and do not necessarily imply causation. We have discussed how the
parameters of regression and logistic regression models relate to simple descriptive statistics and
how they may be interpreted for some relatively simple models.