Literature DB >> 32831627

Accounting for study participants who are ineligible for linkage: a multiple imputation approach to analyzing the linked National Health and Nutrition Examination Survey and Centers for Medicare and Medicaid Services' Medicaid data.

Jennifer Rammon1, Yulei He1, Jennifer D Parker1.   

Abstract

Data from the National Health and Nutrition Examination Survey have been linked to the Center for Medicare and Medicaid Services' Medicaid Enrollment and Claims Files for the survey years 1999-2004. The linked data are produced by the National Center for Health Statistics' (NCHS) Data Linkage Program and are available in the NCHS Research Data Center. This project compares the usefulness of multiple imputation to account for data linkage ineligibility and other survey nonresponse with currently recommended weight adjustment procedures. Estimated differences in environmental smoke exposure across Medicaid/Children's Health Insurance Program (CHIP) enrollment status among children ages 3-15 years are examined as a motivating example. Comparisons are drawn across the three different estimates: one that uses MI to impute the administrative Medicaid/CHIP status of those who are ineligible for linkage, a second that uses the linked data restricted to linkage eligible participants with a basic weight adjustment, and a third that uses self-reported Medicaid/CHIP status from the survey data. The results indicate that estimates from the multiple imputation analysis were comparable to those found when using weight adjustment procedures and had the added benefit of incorporating all survey participants (linkage eligible and linkage ineligible) into the analysis. We conclude that both multiple imputation and weight adjustment procedures can effectively account for survey participants who are ineligible for linkage.

Entities:  

Keywords:  CHIP; Children; Multiple imputation; NHANES Medicaid linked data; Serum cotinine

Year:  2018        PMID: 32831627      PMCID: PMC7437992          DOI: 10.1007/s10742-018-0186-3

Source DB:  PubMed          Journal:  Health Serv Outcomes Res Methodol        ISSN: 1387-3741


  28 in total

1.  A comparison of inclusive and restrictive strategies in modern missing data procedures.

Authors:  L M Collins; J L Schafer; C M Kam
Journal:  Psychol Methods       Date:  2001-12

2.  Validation of self reported smoking.

Authors:  M Rebagliato
Journal:  J Epidemiol Community Health       Date:  2002-03       Impact factor: 3.710

3.  Linkage of NCHS Population Health Surveys to Administrative Records From Social Security Administration and Centers for Medicare Medicaid Services.

Authors:  Cordell Golden; Anne K Driscoll; Alan E Simon; Dean H Judson; Eric A Miller; Jennifer D Parker
Journal:  Vital Health Stat 1       Date:  2015-09

4.  When smokers move out and non-smokers move in: residential thirdhand smoke pollution and exposure.

Authors:  Georg E Matt; Penelope J E Quintana; Joy M Zakarian; Addie L Fortmann; Dale A Chatfield; Eunha Hoh; Anna M Uribe; Melbourne F Hovell
Journal:  Tob Control       Date:  2010-10-30       Impact factor: 7.552

5.  Program Churning and Transfers Between Medicaid and CHIP.

Authors:  Sean M Orzol; Lauren Hula; Mary Harrington
Journal:  Acad Pediatr       Date:  2015 May-Jun       Impact factor: 3.107

Review 6.  Cotinine as a biomarker of environmental tobacco smoke exposure.

Authors:  N L Benowitz
Journal:  Epidemiol Rev       Date:  1996       Impact factor: 6.222

7.  Family hardships and serum cotinine in children with asthma.

Authors:  Adam J Spanier; Andrew F Beck; Bin Huang; Meghan E McGrady; Dennis D Drotar; Roy W A Peake; Mark D Kellogg; Robert S Kahn
Journal:  Pediatrics       Date:  2015-01-12       Impact factor: 7.124

8.  Non-smoking pregnant women and their fetuses are exposed to environmental tobacco smoke as a result of living in multiunit housing.

Authors:  Christina I Orazine; William A Arias; Suzanna R Magee; Ewa King
Journal:  J Expo Sci Environ Epidemiol       Date:  2016-08-03       Impact factor: 5.563

9.  A longitudinal view of child enrollment in Medicaid.

Authors:  Alan E Simon; Anne Driscoll; Yelena Gorina; Jennifer D Parker; Kenneth C Schoendorf
Journal:  Pediatrics       Date:  2013-09-23       Impact factor: 7.124

10.  Data linkage: a powerful research tool with potential problems.

Authors:  Megan A Bohensky; Damien Jolley; Vijaya Sundararajan; Sue Evans; David V Pilcher; Ian Scott; Caroline A Brand
Journal:  BMC Health Serv Res       Date:  2010-12-22       Impact factor: 2.655

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.