A (2) | C (5) | D (8) | E (2) | F (3) | G (4) | I (4) | L (2) | M (6) | N (5) | O (2) | P (2) | R (5) | S (4) | T (2) | U (2) | V (1)
  • Dimension

    The dimensions are the levels of a log frame that define the hierarchical structure. An example of this structure can be seen in the SDGs. This is a two dimensional log frame with the higher dimension of goals consisting of various lower dimension targets. Indicators are usually associated with measuring the lowest dimension. There is no limit to the number of dimensions that ADAPT can handle. However a well-designed lograme will usually be simple and not have more than three dimensions.

  • Disagreggation

    Disagreggation is a key concept in the “no one left behind” agenda. It refers to targets groups for which an indicator is being applied for a cross group comparison. The SDGs have defined their disaggregation levels as: income, sex, age, race, ethnicity, migratory status, disability. Although disagreggation includes geographic, ADAPT handles this separately. For ADAPT disaggregation can be synonymous with “domain of study”. It should be noted that for ADAPT a disagreggation variable is not the same as a design variable. Disagreggation does not imply that the results will be statistically significant at that level.

  • Data source

    A specific data set, metadata set, database or metadata repository from where data or metadata are available. Major data sources are administrative data, micro data (surveys, census, etc.) and big data (large datasets coming from telecom records, etc.).

  • Design variable

    Design variables are the variables that are included in the survey questionnaire/administrative record to categorize the population (e.g. age), and thus could be applied to all indicators calculated from that data source, or used to calculate more complex ones.

  • Data source type

    The type of data source depends on how the data is gathered and the population it intends to represent.

    • Administrative data:  Administrative data is the set of units and data derived from an administrative source.
    • Agricultural surveys:  Agricultural surveys gather data on agricultural activity, providing a picture of agriculture land use and production.  
    • Census:  A census is a survey conducted on the full set of observation objects belonging to a given population or universe.
    • Enterprise surveys:  An Enterprise Survey is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of business environment topics including access to finance, corruption, infrastructure, crime, competition, and performance measures.
    • Facility surveys: Facility surveys are conducted in public establishments (e.g. schools) to evaluate the quality of the service that is being provided to the community, to identify needs or to understand the relationship between the provider and the household.
    • HH-surveys:  A household survey is any survey that is administered at the household level.  It collects information about the household and the individuals living in those households.  It includes Living Standards Measurement Study surveys, Integrated Surveys, Priority Surveys, Core Welfare Indicator Questionnaire (CWIQ) surveys, Household Budget Surveys, Labor Force Surveys, Demographic and Health Surveys, education surveys, etc.
    • Other data: all other data sources.

    Sources:  https://stats.oecd.org/glossary/,  http://econ.worldbank.org/,  http://www.enterprisesurveys.org/methodology

  • Design

    The design of a data source refers to the population characteristics for which it seeks to detect a disaggregated effect.