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This report shows how to apply the calibration-weighting procedures in SAS-callable SUDAAN (Version 11) to a stratified simple random sample drawn from a complete list frame for an establishment survey. The results are calibrated weights produced via raking, raking to a size variable, and pseudo-optimal calibration that potentially reduce and appropriately measure the standard errors of estimated totals. The report then shows how to use these procedures to remove selection bias caused by unit nonresponse under a plausible response model. Although unit nonresponse is usually assumed to be a function of variables with known population or full-sample estimated totals, calibration weighting can often be used when nonresponse is assumed to be a function of a variable known only for unit respondents (i.e., not missing at random). When producing calibrated weights for an establishment survey, one advantage the SUDAAN procedures have over most of their competitors is that their linearization-based variance estimators can capture the impact of finite-population correction.

Calibration-Weighting a Stratified Simple Random Sample with SUDAAN