title: Comparison of logistic regression and neural network analysis applied to predicting living setting after hip fracture.
abstract: OBJECTIVE
  Describe and compare the characteristics of artificial neural networks and logistic regression to develop prediction models in epidemiological research.
  
  
  METHODS
  The sample included 3708 persons with hip fracture from 46 different states included in the Uniform Data System for Medical Rehabilitation. Mean age was 75.5 years (sd=14.2), 73.7% of patients were female, and 82% were non-Hispanic white. Average length of stay was 17.0 days (sd=10.6). The primary outcome measure was living setting (at home vs. not at home) at 80 to 180 days after discharge.
  
  
  RESULTS
  Statistically significant variables (p <.05) in the logistic model included follow-up therapy, sphincter control, self-care ability, marital status, age, and length of stay. Areas under the receiver operating characteristic curves were 0.67 for logistic regression and 0.73 for neural network analysis. Calibration curves indicated a slightly better fit for the neural network model.
  
  
  CONCLUSIONS
  Follow-up therapy and independent bowel and/or bladder function were strong predictors of living at home up to 6 months after hospitalization for hip fracture. No practical differences were found between the predictive ability of logistic regression and neural network analysis in this sample.
authors.affiliation: Division of Rehabilitation Sciences, University of Texas Medical Branch, Galveston, TX 77555-1137, USA. kottenba@utmb.edu
authors.forename: Kenneth J
authors.initials: KJ
authors.lastname: Ottenbacher
authors.forename: Richard T
authors.initials: RT
authors.lastname: Linn
authors.forename: Pamela M
authors.initials: PM
authors.lastname: Smith
authors.forename: Sandra B
authors.initials: SB
authors.lastname: Illig
authors.forename: Melodee
authors.initials: M
authors.lastname: Mancuso
authors.forename: Carl V
authors.initials: CV
authors.lastname: Granger
mesh_terms: D000368:Aged; D000465:Algorithms; D005260:Female; D005500:Follow-Up Studies; D006615:Hip / Q000503:physiopathology; D006620:Hip Fractures / Q000208:ethnology / Q000534:rehabilitation* / Q000628:therapy; D006801:Humans; D007348:Insurance, Health; D007902:Length of Stay; D016015:Logistic Models; D008297:Male; D017533:Marital Status; D008875:Middle Aged; D015999:Multivariate Analysis; D016571:Neural Networks, Computer; D016896:Treatment Outcome