title: Clinical research: benefits of Bhattacharya modeling.
abstract: BACKGROUND
  Bhattacharya modeling is a Gaussian method recommended by the Food and Agricultural Organization of the United Nations Guidelines for analyzing the eco-system. It is rarely used in clinical research.
  
  
  OBJECTIVE
  To investigate the performance of Bhattacharya modeling for clinical data analysis.
  
  
  METHODS
  Using as examples simulated vascular lab scores we assessed the performance of the Bhattacharya method. SPSS statistical software is used.
  
  
  RESULTS
  1. The Bhattacharya method better fitted the data from a single sample than did the usual Gaussian curve derived from the mean and standard deviation with 15 vs. 9 cuts. 2. Bhattacharya models demonstrated a significant difference at p < 0.0001 between the data from two parallel-groups, while the usual t-test and Mann-Whitney test were insignificant at p = 0.051 and 0.085. 3. Bhattacharya modeling of a histogram suggestive of certain subsets identified three Gaussian curves.
  
  
  CONCLUSIONS
  We recommend that Bhattacharya modeling be more often considered in clinical research for the purpose of (1) unmasking normal values of diagnostic tests, (2) improving the p-values of data testing and (3) objectively searching subsets in the data.
authors.affiliation: Hospital San Carlos, Playa del Carmen, Mexico.
authors.forename: Manuel C
authors.initials: MC
authors.lastname: Solis
authors.forename: Ton J
authors.initials: TJ
authors.lastname: Cleophas
mesh_terms: D035843:Biomedical Research / Q000379:methods; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D019937:Diagnostic Techniques and Procedures / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D012984:Software; D018709:Statistics, Nonparametric