The 2006-2010 National Survey of Family Growth
sample design and analysis of a continuous survey
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Author
Contributions
- National Center for Health Statistics (U.S.) - Contributor
- National Survey of Family Growth (U.S.) - Contributor
Publication
2010 - U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, Hyattsville, MD, Maryland
Language
English
Word Count
9,000 words, Guess
Page Count
36 pages
Identifiers
- Library of Congress Control Number2010551128
- OCLC Control Number643340432
- Open LibraryOL24807696M
Classifications
- LCCHQ762.U6 A15 2010
Description
"Objective: The National Survey of Family Growth (NSFG) collects data on pregnancy, childbearing, men's and women's health, and parenting from a national sample of women and men 15-44 years of age in the United States. This report describes the sample design for the NSFG's new continuous design and the effects of that design on weighting and variance estimation procedures. A working knowledge of this information is important for researchers who wish to use the data. Two data files are being released the first covering 2.5 years (30 months) of data collection and the second after all data have been collected. This report is being released with the first data file. A later report in this Series will include specific results of the weighting, imputation, and variance estimation. Methods: The NSFG's new design is based on an independent, national probability sample of women and men 15-44 years of age. Fieldwork was carried out by the University of Michigan's Institute for Social Research (ISR) under a contract with the National Center for Health Statistics (NCHS). In-person, face-to-face interviews were conducted by professional female interviewers using laptop computers. Results: Analysis of NSFG data requires the use of sampling weights and estimation of sampling errors that account for the complex sample design and estimation features of the survey. Sampling weights are provided on the data files. The rate of missing data in the survey is generally low. However, missing data were imputed for about 600 key variables (called 'recodes') that are used for most analyses of the survey. Imputation was accomplished using a multiple regression procedure with software called IVEware, available from the University of Michigan website."--p. 1.
Subjects
Series Statement
- Vital and health statistics. Series 2, Data evaluation and methods research -- no. 150
- DHHS publication -- no. (PHS) 2010-1350
- Vital and health statistics -- 150.
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