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WesVar uses the robust and flexible approach of replication variance estimation. Replication methods apply to sample designs and estimators from the simple to the most complex. Using one of five methods of replication, you can estimate standard errors for simple estimators like totals or complicated ones like logistic regression parameter estimates.

WesVar's simple point-and-click interface lets you quickly create weights, specify tables, and define regression models. No coding of procedure statements is necessary.

You can create survey weights using three methods of jackknife replication and two versions of balanced repeated replication. You select the variables that identify strata and primary sampling units and choose a replication method. WesVar creates a set of weights for each replicate subsample. You can then adjust the weights for nonresponse, post-stratify the weights, or rake weights to control totals.

Analysis requests are organized in workbooks that have an intuitive tree structure. Highlighting different nodes in the tree allows you to select the statistics you want, control the appearance of output, set the level of confidence intervals, and specify many other options. Simple dialog boxes let you define complicated functions of estimates in cells of a table and statistics like means, quantiles, and standardized rates.

Regression models are specified with a few mouse clicks or by dragging and dropping variables. Easy-to-use screens let you define customized hypothesis tests and odds ratios.