Guide to Using Masked Design Variables to Estimate Standard Errors in Public Use Files of the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey

Bibliographic Data

ID13774826
AuthorsEsther Hing (0000-0001-8051-9678, National Center for Health Statistics, corresponding author), Sarah Gousen, Iris Shimizu, Catharine W Burt, Catharine Burt
Year2003
Volume40
Issue4
Pages401-415
Publication date2003-11-01
Open AccessYes
TypeARTICLE
VenueINQUIRY The Journal of Health Care Organization Provision and Financing (JOURNAL)
Journal identifiersISSN: 0046-9580 • E-ISSN: 1945-7243
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.5034/inquiryjrnl_40.4.401
PMID15055838
OpenAlexW2076936153
LanguageEN
Citations received3

Until recently, sample design information needed to correctly estimate standard errors from the National Ambulatory Medical Care Survey (NAMCS) and the National Hospital Ambulatory Medical Care Survey (NHAMCS) public use files was not released for confidentiality reasons. In 2002, masked sample design variables were released for the first time with the 1995-2000 NAMCS and NHAMCS public use files. This paper shows how to use masked design variables to compute standard errors in three software applications. It also discusses when masking overstates or understates "in-house" standard errors, and how masking affects the significance levels of point estimates and logistic regression parameters

Ambulatory · Ambulatory care · Computer security · Confidentiality · Family medicine · Health care · Logistic regression · Masking (illustration · Medical care · Medical emergency · National standard · Political science · Sample (material · Standard of care · Statistics · Computer Science · Engineering · Healthcare Policy and Management · Law · Mathematics · Medicine · Surgery

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