Although item nonresponse was very low, missing data were imputed for the 11 items with a response rate less< than 100 percent. The missing items included both numerical data such as number of students in dual enrollment programs, as well as categorical data, such as the academic eligibility requirements for high school students to participate in dual enrollment programs. The missing categorical data were imputed using a "hot- deck" approach to obtain a "donor" institution from which the imputed values were derived. Under the hot- deck approach, a donor institution that matched selected characteristics of the institution with missing data (the recipient institution) was identified (Kalton 1983). The matching characteristics included institution type, control, highest level of offering, and enrollment size. In addition, relevant questionnaire items were used to form appropriate imputation groupings. Once a donor was found, it was used to derive the imputed values for the institution with missing data. For categorical items, the imputed value was simply the corresponding value from the donor institution. For the numerical items, the imputed value was calculated by taking the donor's response for that item and dividing that number by the total number of students enrolled in the donor institution. This ratio was then multiplied by the total number of students enrolled in the recipient institution to provide an imputed value.