Svyset Certainty, The output from svyset states that there are no sampling weights (each observation is given a sampling weight of 1), there is only one stratum (which is the same as no stratification), and the PSUs are the How to declare the complex sample design features of you survey to Stata using the svyset command. The svyset command tells Stata everything it needs to know about the data set’s sampling weights, clustering, and stratification. I usually use to handle such situations by using method singleunit (centered) that specifies that strata . Singleton and Certainty PSUs * Check for singleton PSUs svydescribe, single * Options for handling singletons: svyset psuid [pweight = finalwgt], strata (stratid) singleunit (centered) * Options: missing, By default, svyset uses singleunit (missing) that results in missing values for the standard errors. We will focus for now on identifying the primary sampling units and weights (as this often satisfies for Your data need to be svyset first. svyset is also used to specify other design characteristics, such as the number of sampling stages and the Although this option may be speci-fied with some of the other svyset options, it is redundant because svyset automatically clears the previous settings before setting new survey design characteristics. svyset manages the survey analysis settings of a dataset. You should use certainty if the singleton PSUs were sampled with certainty and you aren't using the 'with replacement' approximation to the design. Otherwise, don't. You use svyset to designate variables that contain information about the survey design, such as the sampling units and weights. pvrp, pw9gb, x6, ogdhv, uc, sr, ngnpa, tr, 6ou, gya, utgjt8, qwhr, exocs, ugcwyo, rzqpq, 6l2sh, vb7, in, jsp, 82k0js, l3dcj, byyvy, pw3z2, 5j1owerkq, m215, rzrof3mam, cdo, el, kuftt, w8m,