This talk discusses Stata's features for analyzing survey data and correlated data, and will explain how and when to use the three major variance estimators for survey and correlated data: the linearization estimator, balanced repeated replications, and the clustered jackknife (the latter two having been added in Stata 9). The talk will also discuss sampling designs and stratification, including Stata's new features for estimation with data from multistage designs and for applying poststratification. A theme of the seminar will be how you can make inferences with correct coverage from data collected by single stage or multistage surveys or from data with inherent correlation, such as data from longitudinal studies.
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