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NAEP Technical DocumentationVariables that Define Groups in NAEP

The variables used to define groups for a given assessment scale (or group of scales) include a broad spectrum of contextual variables and composites of such variables. All standard reporting variables are used in the population-structure models. Results for any variables not used in the models may be biased.

The initial step in the construction of variables used in the scale score distribution models involves forming student-based vectors of response data from answers to student survey questionnairesteacher questionnairesschool questionnaires; demographic and contextual data; and other student information.

The initial vectors concatenate this student contextual information into a series of identifying "contrasts" comprising the following variables and interactions.

  • Categorical variables are derived by expanding the response options of a questionnaire variable into a binary series of one-degree-of-freedom "dummy" variables or contrasts. These form the majority of variables in the vector.
     
  • Demographic variables possess ordinal response options, such as number of hours spent watching television, which are included as linear and/or quadratic multi-degree-of-freedom contrasts. Starting in the 2002 and 2003 assessments, and continuing since then, linear multi-degree-of-freedom contrasts were replaced by binary series of one-degree-of-freedom "dummy" contrasts, and quadratic multi-degree-of-freedom contrasts were removed.
     
  • Continuous variables, such as student enrollment in a school or in a grade within a school, are included as contrasts in their original form or a transformation of their original form.
     
  • Interactions of two or more categorical variables form a set of orthogonal one-degree-of-freedom dummy variables or contrasts.

For each variable in the population-structure model, there is a "missing" category. For example, for the gender variable, the categories are male, female, and missing. "Missing" is coded as one level of a variable in the model.

The specifications used for constructing the variables used in the scale score distribution models are provided, along with a summary. Starting in 2008 and continuing forward, the listing of estimation variables used in the population-structure models are presented in textual format. For more information about NAEP variables, see lists of each variable available by assessment year and subject.

Links to estimation variables used to define groups in NAEP population-structure models: 2000–2018
YearSubject area
2018 Civics
Geography
Technology and engineering literacy (TEL)
U.S. history
2017 Mathematics
Reading
2016 Arts
2015 Mathematics
Reading
Science
2014 Civics
Geography
Technology and engineering literacy (TEL)
U.S. history
2013 Mathematics
Reading
2012 Economics
Mathematics (long-term trend)
Reading (long-term trend)
2011 Mathematics
Reading
Science
Writing
2010 Civics
Geography
U.S. history
2009 Mathematics
Reading
Science
2008 Arts
Mathematics (long-term trend)
Reading (long-term trend)
2007 Mathematics
Reading
Writing
2006 Civics
Economics
U.S. history
2005 Mathematics
Reading
Science
2004 Mathematics (long-term trend)
Reading (long-term trend)
2003 Mathematics
Reading
2002 Reading
Writing
2001 Geography
U.S. history
2000 Mathematics
Reading
Science
NOTE: Because preliminary analyses of students' writing performance in the 2017 NAEP writing assessments at grades 4 and 8 revealed potentially confounding factors in measuring performance, results will not be publicly reported.
SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP), 2000–2018 Assessments.



Last updated 02 November 2022 (SK)