provide inputs to the formula. To these five considerations, we add five others that have emerged during our discussions with data users and producers and through our own examination of the necessary characteristics of data for use in allocating federal funds: (1) fairness, (2) stability from year to year, (3) insensitivity to differences in state policies and methods, (4) transparency, and (5) comparability. The rest of this section describes each of these criteria.

Conceptual Fit A data element used in an allocation formula should meet the conceptual objectives of the program for which the allocation is aimed. In the case of allocating Title III education funds to states, a data element with a good conceptual fit is one that meets the definition provided in the legislation—the number of limited English proficient and immigrant children and youth in a state. In a larger sense, however, considering the overall objective of the allocation of federal funds, a conceptually fitting data element would provide state and local governments with federal funding that is proportional to their need and circumstances.

Level of Geographic Detail The Title III legislation stipulates that the federal funds for the ELL program should be allocated to the states. Thus, the state government is the key level of detail for which the data should be available.

Timeliness The elapsed time between the reference period for the estimates and the period for which the allocations are being made should be as short as possible so that the allocation would appropriately reflect the need at the time that the allocation is made.

Quality Data quality is broadly defined as “fitness for use” (Statistics Canada, 2009, p. 6; Organisation for Economic Co-operation and Development, 2003, p. 6). In turn, fitness for use is generally characterized in terms of six attributes that are expected of the information provided by the data products:

  1. utility: the usefulness of the information to its intended users;

  2. objectivity: whether information is accurate, reliable, and unbiased, and is presented in an accurate, clear, and unbiased manner;

  3. interpretability: the availability of documentation that includes a presentation of the underlying concepts and their definitions; descriptions of the methods used to collect, process, and analyze the data; and a discussion of the limitations imposed by the methods used to aid customers in understanding and using the data;

  4. integrity: the security or protection of information from unauthorized access or revision;

  5. accuracy: the difference between an estimate and its true value, characterized in terms of systematic error or bias, and random error or variance; and

  6. comparability: similarity across geographic and demographic dimensions.

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