| Title: | Secondary Statistical Modeling With the National Assessment of Adult Literacy: Implications for the Design of the Background Questionnaire |
| Description: | With the advent of simple-to-use advanced statistical software packages, it is becoming increasingly easy to specify and estimate complex statistical models for addressing substantive questions in adult literacy and other areas of education. Such problems as the role of literacy in voting behavior or the job market experiences of individuals with GEDs, can be addressed with relative ease. However, a thoughtful application of statistical models to educational data leads to the recognition that certain assumptions must be met for the model estimates to be useful for theoretical explanation and/or policy analysis. The purpose of this paper is to offer recommendations to the National Center for Education Statistics on the development of the background questionnaire for the National Assessment of Adult Literacy. The recommendations presented in this paper are from the viewpoint of a researcher interested in applying sophisticated statistical models to address important issues in adult literacy. This paper focuses on five issues: (1) sampling, (2) selection bias, (3) measurement, (4) policy analysis, and (5) cohort effects. |
| Online Availability: |
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| Cover Date: | March 2000 |
| Web Release: | March 29, 2000 |
| Print Release: | This Publication will only be available online. |
| Publication #: | NCES 200005 General Ordering Information |
| Center/Program: | NCES |
| Authors: | David Kaplan |
| Type of Product: | Working Paper |
| Working Papers provide preliminary analysis of substantive, technical, and methodological issues. They are works in progress that are presented to promote the sharing of valuable work experience and knowledge. These papers have not undergone a rigorous review for consistency with NCES standards. | |
| Survey/Program Areas: |
National Assessments of Adult Literacy (NAAL) |
| Keywords: | |
| Questions: |
For questions about the content of this Working Paper, please contact: Sheida E. White. |
