Early Childhood Longitudinal Survey (ECLS) and National Education Longitudinal Study of 1988 (NELS88)

Early Childhood Longitudinal Survey (ECLS)The Early Childhood Longitudinal Study (ECLS) Program provides national data on children's status at birth and at various points thereafter; children's transitions to nonparental care, early education programs, and school; and children's experiences and growth through the fifth grade. ECLS also provides data to test hypotheses about the effects of a wide range of family, school, community and individual variables on children's development, early learning and early performance in school. Longitudinal Survey and Earlier Longitudinal Surveys (ECLS.)

National Education Longitudinal Study of 1988 (NELS88) A nationally representative sample of eighth-graders were first surveyed in the spring of 1988. A sample of these respondents were then resurveyed through four follow-ups in 1990, 1992, 1994, and 2000. On the questionnaire, students reported on a range of topics including: school, work, and home experiences; educational resources and support; the role in education of their parents and peers; neighborhood characteristics; educational and occupational aspirations; and other student perceptions. Additional topics included self-reports on smoking, alcohol and drug use and extracurricular activities. For the three in-school waves of data collection (when most were eighth-graders, sophomores, or seniors), achievement tests in reading, social studies, mathematics and science were administered in addition to the student questionnaire. National Education Longitudinal Study of 1988 (NELS:88)

A: This means that the standard errors could not be estimated, most likey because of perfect collinearities in the model. The most common error that causes this is creating a set of dummy variables, and including all the dummy variables plus a constant term in the model. When you do this, the sum of the dummy variables equals one (because one of them is always equal to one, so the sum always equals one). Try eliminating one of the dummy variables.