Imputation methods are used to fill in several types of missing data in SIPP. They are used to complete some item nonresponse, person-level nonresponse within households (Type Z nonresponse), and some wave nonresponse (intermittent responses bounded by two responding waves). Imputation fills in gaps in the data set and makes data analyses easier. It also allows more people to be retained as panel members for longitudinal analyses. The concern, however, is that imputation fabricates data to some degree. Treating the imputed values as actual values in estimating the variance of survey estimates leads to an overstatement of the precision of the estimates (Brick and Kalton, 1996). It is important to recognize this fact when sizable proportions of values are imputed.
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