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.
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 desi...
| Publicado en: | Inquiry (00469580) Vol. 40; no. 4; pp. 401 - 416 |
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| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
Winter2003/2004
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=106775431&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 106775431 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00469580 INQ jtl: Inquiry (00469580) issn: 00469580 maglogo: Y pubinfo: dt: Winter2003/2004 vid: 40 iid: 4 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 106775431 106775431 2004154167 10.5034/inquiryjrnl_40.4.401 NLM15055838 106775431 ppf: 401 ppct: 15 formats: tig: atl: 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. aug: au: Hing E Gousen S Shimizu I Burt C affil: Ambulatory Care Statistics Branch, Division of Health Care Statistics, National Center for Health Statistics, 3311 Toledo Road, Room 3409, Hyattsville, MD 20872; ehing@cdc.gov sug: subj: Ambulatory Care Utilization Bias (Research) Emergency Service Utilization Office Visits Utilization Outpatient Service Utilization Surveys Adolescence Adult Aged Child Child, Preschool Cluster Analysis Data Analysis Software Databases Descriptive Statistics Female Infant Infant, Newborn Logistic Regression Male Middle Age Models, Statistical Practitioner's Office Probability Probability Sample Quantitative Studies Random Sample Sampling Error United States Human Adolescent: 13-18 years Adult: 19-44 years Aged: 65+ years Child: 6-12 years Child, Preschool: 2-5 years Infant: 1-23 months Infant, Newborn: birth-1 month Middle Aged: 45-64 years Female Male ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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