Demographic Data as Independent Variables
Tip: When race/ethnicity, gender, or disability status is used as an independent variable, specify the reason for its use and include the reasons in documentation of the results.
Tip: When using a variable as a proxy for another variable, as in using educational level as a proxy for socio-economic status, indicate that the proxy is being used and include a rationale for why this is being done.
Rationale: In educational areas, evaluators may unconsciously accept a pattern of demographic differences in educational achievement or attainment as natural rather than looking for reasons to explain such a pattern. When group membership is accepted as an explanation for a pattern of performance, the truth may be distorted.1
Tip: When interpreting demographic differences, consider such conceptually relevant and possibly confounding factors as socioeconomic status, individual and family educational backgrounds, immigrant status, and place of residence. Where possible include statistical controls.
Rationale: There are large differences by race/ethnicity and disability status in a variety of areas. For example, in 2010, the Census Bureau reported the median household net worth for Whites was $110,729, versus of $7,424 for Hispanic households and $4,995 for Black households.2 Results from the 2006 American Community Survey found significant disparities in the median incomes of those with and without disabilities. Median earnings for people with no disability were over $28,000 compared to the $17,000 median income reported for individuals with a disability.3 Unless such differences are addressed, in any analysis, there is a great danger of generating inaccurate conclusions.
1 Nelson-Barber, S., LaFrance, J., Trumbull, E., & Aburto, S. (2005). Culturally-responsive program evaluation. In S. Hood, R. Hopson, & H. Frierson (Eds.), The role of culture and cultural context: A mandate for inclusion, the discovery of truth and understanding in evaluative theory and practice (pp. 61-85). Greenwich, CT: Information Age Publishing.
2 Luhby, T. (2012). Worsening wealth inequality by race. CNN Money.
3 American Psychological Association. (2013). Disability & Socioeconomic Status.