title: Public health application comparing multilevel analysis with logistic regression: immunization coverage among long-term care facility residents.
abstract: OBJECTIVE
  Public health studies often sample populations using nested sampling plans. When the variance of the residual errors is correlated between individual observations as a result of these nested structures, traditional logistic regression is inappropriate. We used nested nursing home patient data to show that one-level logistic regression and hierarchical multilevel regression can yield different results.
  
  
  METHODS
  We performed logistic and multilevel regression to determine nursing home resident characteristics associated with receiving pneumococcal immunizations. Nursing home characteristics such as type of ownership, immunization program type, and certification were collected from a sample of 249 nursing homes in 14 selected states. Nursing home resident data including demographics, receipt of immunizations, cognitive patterns, and physical functioning were collected on 100 randomly selected residents from each facility.
  
  
  RESULTS
  Factors associated with receipt of pneumococcal vaccination using logistic regression were similar to those found using multilevel regression model with some exceptions. Predictors using logistic regression that were not significant using multilevel regression included race, speech problems, infections, renal failure, legal responsibility for oneself, and affiliation with a chain. Unstable health conditions were significant only in the multilevel model.
  
  
  CONCLUSIONS
  When correlation of resident outcomes within nursing home facilities was not considered, statistically significant associations were likely due to residual correlation effects. To control the probability of type I error, epidemiologists evaluating public health data on nested populations should use methods that account for correlation among observations.
authors.affiliation: Immunization Services Division, National Immunization Program, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA. BFB7@cdc.gov
authors.forename: Barbara H
authors.initials: BH
authors.lastname: Bardenheier
authors.forename: Abigail
authors.initials: A
authors.lastname: Shefer
authors.forename: Lawrence
authors.initials: L
authors.lastname: Barker
authors.forename: Carla A
authors.initials: CA
authors.lastname: Winston
authors.forename: C Kristina
authors.initials: CK
authors.lastname: Sionean
mesh_terms: D000368:Aged; D016021:Epidemiologic Studies; D005260:Female; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D009735:Nursing Homes / Q000191:economics / Q000706:statistics & numerical data*; D010067:Ownership; D022242:Pneumococcal Vaccines / Q000627:therapeutic use*; D011634:Public Health / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D012307:Risk Factors; D016896:Treatment Outcome
chemical_list: D022242:Pneumococcal Vaccines