¹ For more information on the NPSAS survey, consult U.S. Department of Education, National Center for Education Statistics, Methodology Report for the 1999–2000 National Postsecondary Student Aid Study (NCES 2002–152) (Washington, DC: 2001). Additional information is also available at the NPSAS website. (return to text)

² Ibid. (return to text)

³ For nonresponse bias analysis, see U.S. Department of Education, National Center for Education Statistics, National Postsecondary Student Aid Study, 1999–2000 (NPSAS:2000), CATI Nonresponse Bias Analysis Report (NCES 2002–03) (Washington, DC: 2002), available at http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=200203. (return to text)

⁴ For more information on NELS:88/2000, consult U.S. Department of Education, National Center for Education Statistics, National Education Longitudinal Study of 1988: Base-Year to Fourth Follow-up Data File User’s Manual (NCES 2002–323) (Washington, DC: 2002). (return to text)

⁵ In order to meet budgetary constraints, students were subsampled in each follow-up. (return to text)

⁶ Ingals, S. et al. Second Follow-Up: Transcript Component Data File User’s Manual (NCES 95–399). U.S Department of Education, National Center for Education Statistics (Washington DC: 1995). (return to text)

⁷ For more information on the BPS:96/98 survey, consult U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students Longitudinal Study First Follow-up 1996–98, Methodology Report (NCES 2000–157) (Washington, DC: 2000). (return to text)

⁸ For more information on the BPS:1996/2001 survey, consult U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students Longitudinal Study:1996–2001 Methodology Report (NCES 2002–171) (Washington, DC: 2002). (return to text)

⁹ Ibid. (return to text)

¹⁰ None of the survey samples were based on simple random sampling procedures and, therefore, simple random sample techniques for estimating sampling error cannot be applied to these data. The DAS takes into account the complexity of the sampling procedures and calculates standard errors appropriate for such samples. The method for computing sampling errors used by the DAS involves approximating the estimator by the linear terms of a Taylor series expansion. The procedure is typically referred to as the Taylor series method. (return to text)

¹¹ A Type I error occurs when one concludes that a difference observed in a sample reflects a true difference in the population from which the sample was drawn, when no such true difference is present. (return to text)

¹² U.S. Department of Education, National Center for Education Statistics, A Note from the Chief Statistician, no. 2, 1993. (return to text)

¹³ Ibid. (return to text)

¹⁴ See Snedecor, G. and Cochran, W. Statistical Methods (Ames, IA: Iowa State University Press, 1980, p. 234); or Harris, R. A Primer of Mulitivariate Statistics (New York: Academic Press, 1975, p. 11). (return to text)

¹⁵ More information about ANOVA and significance testing using the F statistic can be found in any standard textbook on statistical methods in the social and behavioral sciences. (return to text)

¹⁶ For more information about least squares regression, see Michael S. Lewis-Beck, Applied Regression: An Introduction, Vol. 22 (Beverly Hills, CA: Sage Publications, Inc., 1980); William D. Berry and Stanley Feldman, Multiple Regression in Practice, Vol. 50 (Beverly Hills, CA: Sage Publications, Inc., 1987). (return to text)

¹⁷ For more information about commonality analysis, see F. Kerlinger and E. Pedhauzer, Multiple Regression in Behavioral Research (Holt, Rinehart, and Winston Inc., 1973). (return to text)

¹⁸ See John H. Aldrich and Forrest D. Nelson, “Linear Probability, Logit and Probit Models” (Quantitative Applications in Social Sciences, Vol. 45) (Beverly Hills, CA: Sage, 1984). Analysts who wish to estimate other types of models can apply for a restricted data license from NCES. (return to text)

¹⁹ See for example, Goodman, L.A., “The Relationship Between Modified and Usual Multiple-Regression Approaches to the Analysis of Dichotomous Variables”; pp. 83-110 in David Hoise ed., Sociolgical Methodology (San Francisco: Jossey-Bass, 1976), and Knoke, D. “A Comparison of Log-Linear and Regression Models for Systems of Dichotomous Variables” (Sociological Methods and Research, Vol. 3: Sage, 1975). (return to text)

²⁰ The adjustment procedure and its limitations are described in C.J. Skinner, D. Holt, and T.M.F. Smith, eds., Analysis of Complex Surveys (New York: John Wiley & Sons, 1989). (return to text)