Studies of Welfare Populations: Data Collection and Research Issues. Part II: Administrative Data

06/01/2002

This paper addresses the cleaning and linking of individual-level administrative data for the purposes of social program research and evaluation. We will define administrative data as that collected in the course of programmatic activities for the purposes of client-level tracking, service provision, or decision making--essentially, nonresearch activities. Although some data sets are collected with both programmatic and research activities in mind--birth certificates are a good example--researchers usually think of administrative data as a secondary data source in contrast to surveys that are conducted solely for research purposes.

When we refer to administrative data to be used for research and evaluation of social programs, we are referring primarily to data from management information systems designed to assist in the administration of participant benefits, including, income maintenance, food stamps, Medicaid, nutritional programs, child support, child protective services, childcare subsidies, Social Security programs, and an array of social services and public health programs. Because the focus of the research is often on individual well-being, most government social programs aimed at individuals could be included.

Before these administrative data can be used for research purposes, cleaning the data is a major activity as it is in conducting and using any large social surveys. Cleaning is necessary because there are numerous sources of potential error in the data and because the data are not formatted in a way that is easily analyzed by social scientists. We take a broad view of cleaning. It is not just correcting "dirty" data; it is producing a clean data set from a messy assortment of data sets. In this paper, cleaning refers to the entire process of transforming the data as it exists in the information system into an analytic data set.

Record linkage is a major activity in the use of administrative data, especially if the research is longitudinal--and, by definition, evaluation nearly always is. Record linkage is the process of determining that two data records belong to the same individual. Being able to track an individual from one time to the next or across numerous data sets is nearly always necessary when using administrative data, especially because, in most cases, one does not have access to the independent sources of data that can assure that a time 1 measurement and time 2 measurement are of the same person or that an agency 1 record and agency 2 record are for the same individual.(1)

Data cleaning and record linkage are closely related activities. At its most simple level, record linkage is necessary to determine if any duplicate records exist for a single individual or case in a particular data set. Record linkage is used to produce clean, comprehensive data sets from single program data sets. Without accurate record linkage, it is likely that the data on an individual will be incomplete or contain data that do not belong to that individual. And, to do accurate record linkage, the data fields necessary to perform the linkage, typically individual identifiers, must be accurate and in a standardized format across all the data sets to be linked.

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