Exact logistic regression and its performance to SAS system.
- Author:
Qi-jun LIU
1
;
Qing ZENG
;
Yan-rong ZHOU
Author Information
- Publication Type:Journal Article
- MeSH: Adult; Breast Neoplasms; epidemiology; pathology; China; epidemiology; Female; Humans; Logistic Models; Middle Aged; Monte Carlo Method; Prognosis; Software
- From: Chinese Journal of Epidemiology 2003;24(8):725-728
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo 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.
METHODSData from 37 postoperative breast cancer cases were analyzed in 1997 by exact logistic regression under SAS system.
RESULTSData 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.
CONCLUSIONExact 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.