title: Predicting academic success in the first year of chiropractic college.
abstract: OBJECTIVE
  To determine if any existent preadmission academic or personal variables predict academic success in the first year of the Palmer College of Chiropractic West (PCCW) program.
  
  
  METHODS
  One hundred ninety-two students at PCCW who had completed the first year of the program.
  
  
  METHODS
  One-way analysis of variance and stepwise linear multiple regression.
  
  
  RESULTS
  Men had a significantly higher mean matriculating grade point average (MatGPA) than women, but no such relationship existed in the cumulative year-1 GPA (Y1GPA). There was no statistically significant difference in MatGPA for students possessing a degree compared to those without a degree, but degree-holding students had a significantly higher Y1GPA. There was no statistically significant difference in MatGPA for students born in English-speaking countries compared to students born in non-English-speaking countries, but those born in English-speaking countries had a significantly higher Y1GPA. MatGPA, physics GPA, and chemistry GPA provided the strongest regression model, eliciting an R(2) value of 0.327.
  
  
  CONCLUSIONS
  Student characteristics on entering PCCW may help predict student performance in the first academic year. A relatively strong and statistically significant prediction model for Y1GPA (R(2) = 0.327) exists for PCCW. Used in conjunction with other available empirical data, this regression model may allow the institution to make more informed decisions when selecting students for admission.
authors.affiliation: Palmer College of Chiropractic West, Palmer Center for Chiropractic Research, 90 E. Tasman Drive, San Jose, CA 95134, USA. Green_B@palmer.edu
authors.forename: Bart N
authors.initials: BN
authors.lastname: Green
authors.forename: Claire D
authors.initials: CD
authors.lastname: Johnson
authors.forename: Kevin
authors.initials: K
authors.lastname: McCarthy
mesh_terms: D000124:Achievement; D000704:Analysis of Variance; D002684:Chiropractic / Q000193:education*; D004521:Educational Measurement; D004522:Educational Status; D005260:Female; D005544:Forecasting; D006801:Humans; D007802:Language; D008297:Male; D012044:Regression Analysis