title: Combining information from multiple surveys to enhance estimation of measures of health.
abstract: Survey estimates are often affected by non-sampling errors due to missing data, coverage error, and measurement or response error. Such non-sampling errors can be difficult to assess, and possibly correct for, using information from a single survey. Thus, combining information from multiple surveys can be beneficial. In addition, combining information from multiple surveys can help to reduce sampling error. This article describes four examples of projects undertaken by researchers within and outside the National Center for Health Statistics of the Centers for Disease Control and Prevention, in which information from multiple surveys was combined to adjust for non-sampling errors and thereby enhance estimation of various measures of health. The four projects can be described briefly as follows: (1) combining estimates from a survey of households and a survey of nursing homes to extend coverage; (2) using information from an interview survey to bridge the transition in race reporting in the United States census; (3) combining information from an examination survey and an interview survey to improve on analyses of self-reported data; and (4) combining information from two interview surveys to enhance small-area estimation. The article highlights the goals, techniques, and results from the four projects and discusses issues that can arise when information is combined from multiple surveys. Published in 2007 by John Wiley & Sons, Ltd.
authors.affiliation: National Center for Health Statistics, Hyattsville, MD 20782, USA. nschenker@cdc.gov
authors.forename: Nathaniel
authors.initials: N
authors.lastname: Schenker
authors.forename: Trivellore E
authors.initials: TE
authors.lastname: Raghunathan
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000453:epidemiology; D003627:Data Interpretation, Statistical; D006306:Health Surveys; D006801:Humans; D007407:Interviews as Topic / Q000592:standards; D008297:Male; D044469:Racial Groups; D017062:Small-Area Analysis; D014481:United States