Sample design, sampling weights, imputation, and variance estimation in the 1995 National Survey of Family Growth.

F. J. Potter, V. G. Iannacchione, W. D. Mosher, R. E. Mason, J. D. Kavee

Research output: Contribution to journalArticle

Abstract

OBJECTIVES: Cycle 5 of the National Survey of Family Growth (NSFG) was conducted by the National Center for Health Statistics (NCHS) in 1995. The NSFG collects data on pregnancy, childbearing, and women's health from a national sample of women 15-44 years of age. This report describes how the sample was designed, shows response rates for various subgroups of women, describes how the sampling weights were computed to make national estimates possible, shows how missing data were imputed for a limited set of key variables, and describes the proper ways to estimate sampling errors from the NSFG. The report includes both nontechnical summaries for readers who need only general information and more technical detail for readers who need an in-depth understanding of these topics. METHODS: The 1995 NSFG was based on a national probability sample of women 15-44 years of age in the United States and was drawn from 14,000 households interviewed in the 1993 National Health Interview Survey (NHIS). Of the 13,795 women eligible for the NSFG, 10,847 (79 percent) gave complete interviews. RESULTS: This report recommends using weighted data for analysis and a software package that will estimate sampling errors from complex samples (for example, SUDAAN or comparable software). The rate of missing data in the 1995 NSFG was very low. However, missing data were imputed for 315 key variables, called "recodes." Of the 315 recodes defined for Cycle 5, 271 variables had missing data on less than 1 percent of the cases; only 44 had 1 percent or more with missing data. These missing values were imputed for all of these 315 variables. The imputation procedures are described in this report.

Original languageEnglish (US)
Pages (from-to)1-63
Number of pages63
JournalVital and health statistics. Series 2, Data evaluation and methods research
Issue number124
StatePublished - Feb 1998

ASJC Scopus subject areas

  • Statistics and Probability
  • Health Information Management

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