title: A multilevel analysis of the relationships between selected examinee characteristics and United States Medical Licensing Examination Step 2 Clinical Knowledge performance: revisiting old findings and asking new questions.
abstract: BACKGROUND
  This study examines: (1) the relationships between examinee characteristics and United States Medical Licensing Examination Step 2 Clinical Knowledge (CK) performance; (2) the effect of gender and examination timing (time per item) on the relationship between Steps 1 and 2 CK; and (3) the effect of school characteristics on the relationships between examinee characteristics and Step 2 CK performance.
  
  
  METHODS
  A series of hierarchical linear models (examinees-nested-in-schools) predicting Step 2 CK scores was fit to the data set. The sample included 54,487 examinees from 114 U.S. Liaison Committee on Medical Education-accredited medical schools.
  
  
  RESULTS
  Consistent with past examinee-level research, women generally outperformed men on Step 2 CK, and examinees who received more time per item generally outperformed examinees who received less time per item. Step 1 score was generally more strongly associated with Step 2 CK performance for men and for examinees who received less time per item. School-level characteristics (size, average Step 1 performance) influenced the relationship between Steps 1 and 2 CK.
  
  
  CONCLUSIONS
  Both examinee-level and school-level characteristics are important for understanding Step 2 CK performance.
authors.affiliation: National Board of Medical Examiners, 3750 Market St., Philadelphia, Pennsylvania 19104, USA. mcuddy@nbme.org
authors.forename: Monica M
authors.initials: MM
authors.lastname: Cuddy
authors.forename: David B
authors.initials: DB
authors.lastname: Swanson
authors.forename: Gerard F
authors.initials: GF
authors.lastname: Dillon
authors.forename: Matthew C
authors.initials: MC
authors.lastname: Holtman
authors.forename: Brian E
authors.initials: BE
authors.lastname: Clauser
mesh_terms: D005260:Female; D006801:Humans; D008007:Licensure, Medical / Q000592:standards* / Q000706:statistics & numerical data / Q000639:trends; D016014:Linear Models; D008297:Male; D014481:United States