title: [Exact logistic regression and its performance to SAS system].
abstract: OBJECTIVE
  To explore the feasibility of exact logistic regression, used as a complemental method for the maximum liklihood estimation, and to analyse with data small sample, unbalanced structure and highly stratal nature under the situations of questionable results or inexistence of the maximum likelihood estimation.
  
  
  METHODS
  Data from 37 postoperative breast cancer cases were analyzed in 1997 by exact logistic regression under SAS system.
  
  
  RESULTS
  Data calculated by SAS software showed that Quasi-complete separation of data points was detected but the results of maximum likelihood estimation did not exist, SAS outputs conflicted the results of the last maximum likelihood iteration (likelihood Chi-square and score Chi-square have similar P, less than 0.05, but the Wald chi-square had a larger P, more than 0.05). Under conditional exact parameter estimation, it appeared that: (1) the joint effect of conditional score statistics was 21.12 with P = 0.000 3; (2) for individual parameters, the effect conditional score statistics of histological classification (grades) was 5.80 with P = 0.020 8; axillary node metastasis (diversion) was 5.74 with P = 0.019 5; tumor size (size) was 0.79, with P = 0.647 6. The effects of tumor histological classification and axillary node metastasis were statistically significant on breast cancer tumour.
  
  
  CONCLUSIONS
  Exact logistic regression seemed to be a very useful method in analyzing data from small sample when the maximum likelihood estimation was either with no effect or did not exist.
authors.affiliation: Department of Health Statistics, Chongqing University of Medical Sciences, Chongqing 400016, China.
authors.forename: Qi-jun
authors.initials: QJ
authors.lastname: Liu
authors.forename: Qing
authors.initials: Q
authors.lastname: Zeng
authors.forename: Yan-rong
authors.initials: YR
authors.lastname: Zhou
mesh_terms: D000328:Adult; D001943:Breast Neoplasms / Q000453:epidemiology* / Q000473:pathology; D002681:China / Q000453:epidemiology; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D009010:Monte Carlo Method; D011379:Prognosis; D012984:Software