Identifying a parsimonious model for predicting academic achievement in undergraduate medical education: A confirmatory factor analysis

Syeda Kauser Ali, Lubna Ansari Baig, Claudio Violato, Onaiza Zahid

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Objectives: This study was conducted to adduce evidence of validity for admissions tests and processes and for identifying a parsimonious model that predicts students’ academic achievement in Medical College. Methods: Psychometric study done on admission data and assessment scores for five years of medical studies at Aga Khan University Medical College, Pakistan using confirmatory factor analysis (CFA) and structured equation modeling (SEM). Sample included 276 medical students admitted in 2003, 2004 and 2005. Results: The SEM supported the existence of covariance between verbal reasoning, science and clinical knowledge for predicting achievement in medical school employing Maximum Likelihood (ML) estimations (n=112). Fit indices: X2 (21) = 59.70, p =<.0001; CFI=.873; RMSEA = 0.129; SRMR = 0.093. Conclusions: This study shows that in addition to biology and chemistry which have been traditionally used as major criteria for admission to medical colleges in Pakistan; mathematics has proven to be a better predictor for higher achievements in medical college.

Original languageEnglish (US)
Pages (from-to)903-908
Number of pages6
JournalPakistan Journal of Medical Sciences
Volume33
Issue number4
DOIs
StatePublished - Jul 1 2017

Keywords

  • MCAT
  • Medical education
  • Pakistan
  • Psychometrics
  • Structural equation modeling

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