Name: NCES_PIAAC_SKILLSMAP_COUNTY_2017

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Description: The indirect estimates provided in this service were created using a sophisticated statistical method generally referred to as small area estimation (SAE). SAE is a model-dependent approach that produces indirect estimates for areas where survey data is inadequate for direct estimation. SAE models assume that counties with similar demographics would have similar estimates of skills. An estimate for a county then “borrows strength” across related small areas through auxiliary information to produce reliable indirect estimates for small areas. The models rely on covariates available at the small areas, and PIAAC survey data. In the absence of any other proficiency assessment data for individual states and counties, the estimates provide a general picture of proficiency for all states and counties. In addition to the indirect estimates, this website provides precision estimates and facilitates statistical comparisons among states and counties. For technical details on the SAE approach applied to PIAAC, see section 5 of the State and County Estimation Methodology Report.The U.S. state and county indirect estimates reported on this site are not directly comparable with the direct estimates for PIAAC countries that are reported by the Organization for Economic Cooperation and Development (OECD). Specifically, the U.S. state and county indirect estimates (1) represent modeled estimates for adults ages 16-74 whereas the OECD’s direct estimates for participating countries represent estimates for adults ages 16-65, (2) include data for “literacy-related nonresponse” (i.e., adults whose English language skills were too low to participate in the study) whereas the OECD’s direct estimates for countries exclude these data, and (3) are based on three combined data collections (2012/2014/2017) whereas OECD’s direct estimates are based on a single data collection.Similarly, the U.S. national indirect estimates reported on this site are not directly comparable with the direct estimates for the U.S. The U.S. national indirect estimates are derived as an aggregation of the U.S. state and county indirect estimates. In addition, the U.S. national indirect estimates include data for “literacy-related nonresponse” (i.e., adults whose English language skills were too low to participate in the study) whereas the U.S. PIAAC direct estimates exclude these data.

Copyright Text: PIAAC

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Fields:

• OBJECTID_1 ( type: esriFieldTypeOID, alias: OBJECTID_1 )
• Shape ( type: esriFieldTypeGeometry, alias: Shape )
• STATEFP ( type: esriFieldTypeString, alias: STATEFP, length: 2 )
• State ( type: esriFieldTypeString, alias: State name (only applies to "County" and "State" tab), length: 255 )
• Lit_P1 ( type: esriFieldTypeDouble, alias: Literacy proportion at or below Level 1 indirect estimates )
• Lit_P1_CI_L ( type: esriFieldTypeDouble, alias: Lower credible interval bound for literacy proportion at or below Level 1 indirect estimates )
• Lit_P1_CI_U ( type: esriFieldTypeDouble, alias: Upper credible interval bound for literacy proportion at or below Level 1 indirect estimates )
• Lit_P1_CV ( type: esriFieldTypeDouble, alias: Coefficient of variation for literacy proportion at or below Level 1 indirect estimates )
• Lit_P1_CI_L_indicator ( type: esriFieldTypeString, alias: Indicator of zero estimates for literacy proportion at or below Level 1 indirect estimates lower credible interval bound (1=round to 0; 2=negative and set to 0), length: 255 )
• Lit_P2 ( type: esriFieldTypeDouble, alias: Literacy proportion at Level 2 indirect estimates )
• Lit_P2_CI_L ( type: esriFieldTypeDouble, alias: Lower credible interval bound for literacy proportion at Level 2 indirect estimates )
• Lit_P2_CI_U ( type: esriFieldTypeDouble, alias: Upper credible interval bound for literacy proportion at Level 2 indirect estimates )
• Lit_P2_CV ( type: esriFieldTypeDouble, alias: Coefficient of variation for literacy proportion at Level 2 indirect estimates )
• Lit_P3 ( type: esriFieldTypeDouble, alias: Literacy proportion at or above Level 3 indirect estimates )
• Lit_P3_CI_L ( type: esriFieldTypeDouble, alias: Lower credible interval bound for literacy proportion at or above Level 3 indirect estimates )
• Lit_P3_CI_U ( type: esriFieldTypeDouble, alias: Upper credible interval bound for literacy proportion at or above Level 3 indirect estimates )
• Lit_P3_CV ( type: esriFieldTypeDouble, alias: Coefficient of variation for literacy proportion at or above Level 3 indirect estimates )
• Lit_P3_indicator ( type: esriFieldTypeString, alias: Indicator of zero estimates for literacy proportion at or above Level 3 indirect estimates (1=round to 0; 2=negative and set to 0), length: 255 )
• Lit_P3_CI_L_indicator ( type: esriFieldTypeString, alias: Indicator of zero estimates for literacy proportion at or above Level 3 indirect estimates lower credible interval bound (1=round to 0; 2=negative and set to 0), length: 255 )
• Lit_A ( type: esriFieldTypeDouble, alias: Literacy average score indirect estimates )
• Lit_A_CI_L ( type: esriFieldTypeDouble, alias: Lower credible interval bound for literacy average score indirect estimates )
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• Num_P1 ( type: esriFieldTypeDouble, alias: Numeracy proportion at or below Level 1 indirect estimates )
• Num_P1_CI_L ( type: esriFieldTypeDouble, alias: Lower credible interval bound for numeracy proportion at or below Level 1 indirect estimates )
• Num_P1_CI_U ( type: esriFieldTypeDouble, alias: Upper credible interval bound for numeracy proportion at or below Level 1 indirect estimates )
• Num_P1_CV ( type: esriFieldTypeDouble, alias: Coefficient of variation for numeracy proportion at or below Level 1 indirect estimates )
• Num_P2 ( type: esriFieldTypeDouble, alias: Numeracy proportion at Level 2 indirect estimates )
• Num_P2_CI_L ( type: esriFieldTypeDouble, alias: Lower credible interval bound for numeracy proportion at Level 2 indirect estimates )
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• Num_P3 ( type: esriFieldTypeDouble, alias: Numeracy proportion at or above Level 3 indirect estimates )
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• Num_A_CI_U ( type: esriFieldTypeDouble, alias: Lower credible interval bound for numeracy average score indirect estimates )
• Num_A_CV ( type: esriFieldTypeDouble, alias: Coefficient of variation for numeracy average score indirect estimates )
• POP ( type: esriFieldTypeInteger, alias: Total Population )
• POP_TARGET ( type: esriFieldTypeInteger, alias: Target population: population between age 16-74 )
• Male ( type: esriFieldTypeDouble, alias: Proportion of population who are male )
• Female ( type: esriFieldTypeDouble, alias: Proportion of population who are female )
• White ( type: esriFieldTypeDouble, alias: Proportion of population who are White alone )
• Black ( type: esriFieldTypeDouble, alias: Proportion of population who are Black or African American alone )
• Hispanic ( type: esriFieldTypeDouble, alias: Proportion of population who are Hispanic )
• Asian ( type: esriFieldTypeDouble, alias: Proportion of population who are Asian alone )
• AIAN ( type: esriFieldTypeDouble, alias: Proportion of population who are American Indian or Alaska Native alone )
• NHPI ( type: esriFieldTypeDouble, alias: Proportion of population who are Native Hawaiian or Other Pacific Islander alone )
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• COUNTYFP ( type: esriFieldTypeString, alias: COUNTYFP, length: 3 )
• COUNTYNS ( type: esriFieldTypeString, alias: COUNTYNS, length: 8 )
• GEOID ( type: esriFieldTypeString, alias: GEOID, length: 5 )
• County ( type: esriFieldTypeString, alias: County name (only applies to "County" tab), length: 255 )

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