Fixing the nonconvergence bug in logistic regression with SPLUS and SAS

Computer Methods and Programs in Biomedicine
Georg Heinze, Meinhard Ploner

Abstract

When analyzing clinical data with binary outcomes, the parameter estimates and consequently the odds ratio estimates of a logistic model sometimes do not converge to finite values. This phenomenon is due to special conditions in a data set and known as 'separation'. Statistical software packages for logistic regression using the maximum likelihood method cannot appropriately deal with this problem. A new procedure to solve the problem has been proposed by Heinze and Schemper (Stat. Med. 21 (2002) pp. 2409-3419). It has been shown that unlike the standard maximum likelihood method, this method always leads to finite parameter estimates. We developed a SAS macro and an SPLUS library to make this method available from within one of these widely used statistical software packages. Our programs are also capable of performing interval estimation based on profile penalized log likelihood (PPL) and of plotting the PPL function as was suggested by Heinze and Schemper (Stat. Med. 21 (2002) pp. 2409-3419).

References

Nov 5, 1997·Epidemiology·B FoxmanS Spear
Feb 21, 2002·Computer Methods and Programs in Biomedicine·Georg Heinze, Meinhard Ploner
Sep 5, 2002·Statistics in Medicine·Georg Heinze, Michael Schemper

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Citations

Apr 6, 2006·Injury Prevention : Journal of the International Society for Child and Adolescent Injury Prevention·M MartinK Quinlan
Apr 16, 2011·American Journal of Public Health·Alexander C TsaiSheri D Weiser
Oct 15, 2011·The Science of the Total Environment·Alfred E PinkneyMichael A Rutter
Jun 9, 2009·Conservation Biology : the Journal of the Society for Conservation Biology·C Scott FindlayLinda Burr
Jan 13, 2006·Statistics in Medicine·Georg Heinze, Michael Schemper
Feb 21, 2006·Statistics in Medicine·Shelley B BullSophia S F Lee
May 27, 2015·Statistics in Medicine·Sander Greenland, Mohammad Ali Mansournia
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