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 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.
Hing
Esther
E
Ambulatory Care Statistics Branch, Division of Health Care Statistics, National Center for Health Statistics, Hyattsville, MD 20872, USA. ehing@cdc.gov
Gousen
Sarah
S
Shimizu
Iris
I
Burt
Catharine
C
D000293:Adolescent; D000328:Adult; D000368:Aged; D000553:Ambulatory Care / Q000706:statistics & numerical data*; D015982:Bias; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D003625:Data Collection / Q000379:methods; D003628:Database Management Systems; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D019538:Health Care Surveys / Q000379:methods* / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009309:National Center for Health Statistics, U.S.; D009819:Office Visits / Q000706:statistics & numerical data*; D010044:Outpatient Clinics, Hospital / Q000706:statistics & numerical data*; D011336:Probability; D014481:United States