title: Logistic regression analysis to predict Medical Licensing Examination of Thailand (MLET) Step1 success or failure.
abstract: BACKGROUND
  The aim of this paper was to assess factors that predict students' performance in the Medical Licensing Examination of Thailand (MLET) Step1 examination. The hypothesis was that demographic factors and academic records would predict the students' performance in the Step1 Licensing Examination.
  
  
  METHODS
  A logistic regression analysis of demographic factors (age, sex and residence) and academic records [high school grade point average (GPA), National University Entrance Examination Score and GPAs of the pre-clinical years] with the MLET Step1 outcome was accomplished using the data of 117 third-year Ramathibodi medical students.
  
  
  RESULTS
  Twenty-three (19.7%) students failed the MLET Step1 examination. Stepwise logistic regression analysis showed that the significant predictors of MLET Step1 success/failure were residence background and GPAs of the second and third preclinical years. For students whose sophomore and third-year GPAs increased by an average of 1 point, the odds of passing the MLET Step1 examination increased by a factor of 16.3 and 12.8 respectively. The minimum GPAs for students from urban and rural backgrounds to pass the examination were estimated from the equation (2.35 vs 2.65 from 4.00 scale).
  
  
  CONCLUSIONS
  Students from rural backgrounds and/or low-grade point averages in their second and third preclinical years of medical school are at risk of failing the MLET Step1 examination. They should be given intensive tutorials during the second and third pre-clinical years.
authors.affiliation: Department of Community Medicine, Faculty of Medicine, Ramathibodi Hospital, Bangkok, Thailand. grswr@mahidol.ac.th
authors.forename: Samkaew
authors.initials: S
authors.lastname: Wanvarie
authors.forename: Boonmee
authors.initials: B
authors.lastname: Sathapatayavongs
mesh_terms: D000328:Adult; D004501:Education, Medical / Q000592:standards*; D005260:Female; D006801:Humans; D008007:Licensure, Medical / Q000706:statistics & numerical data*; D008297:Male; D011379:Prognosis; D012044:Regression Analysis; D012189:Retrospective Studies; D012846:Singapore; D013337:Students, Medical