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Selecting risk factors: A comparison of discriminant analysis, logistic regression and cox's regression model using data from the tromsø heart study
Author(s) -
Brenn Tormod,
Arnesen Egil
Publication year - 1985
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780040403
Subject(s) - linear discriminant analysis , logistic regression , proportional hazards model , stepwise regression , discriminant , statistics , regression analysis , optimal discriminant analysis , logistic model tree , mathematics , survival analysis , artificial intelligence , computer science
For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20–49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time‐saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non‐stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.