Abstract
Conditional logistic regression models have been extensively used in the field of medicine and mainly applied in matched case control studies. However, none of the major statistical packages, i.e. SAS, MINITAB, SPSS provide diagnostics to assess the goodness-of-fit of these models. In addition the freely downloadable package R provides no functions for this purpose. The objectives of this study are to review the available diagnostics for software for testing goodness-of-fit of conditional logistic regression models by the development of a computer programme and to test this programme which implements some of the reviewed methods on real data. The computer programme is implemented using Visual Basic for Applications (VBA) for Microsoft Excel and connected to the Statistical Analysis Software (SAS) version 9.1 using the Object Linking and Embedding (OLE) automation. The software thus developed is tested on a matched case control study on endometrial cancer. A conditional logistic regression model is fitted to these data and the risk factors for endometrial cancer are identified. MINITAB and SPSS are incapable of doing conditional logistic regression. For testing goodness of the fitted model Proc Logistic in SAS is only capable of giving delta-beta plots which explain the influence of each observation on the parameters of the model. Besides, plots obtained from the developed computer programme, in addition provide information on stratum specific lack-of-fit statistics. These plots were very successful in identifying 3 outlying strata which were quite different from the other strata. In these 3 strata the case had not received estrogen whereas one or more control had received estrogen. Keywords: Conditional logistic regression, dynamic data exchange (DDE), goodness-of-fit, matched case control studies, Object Linking and Embedding (OLE) automation. Doi: 10.4038/jnsfsr.v39i1.2919 J.Natn.Sci.Foundation Sri Lanka 2011 39 (1): 13-23
Highlights
Logistic regression is widely used in both types of observational studies.According to previous studies (Schlesselman,1982; Collett, 2003), logistic models have been extensively used in the field of medicine, and mainly applied in matched case control studies
The odds of having endometrial cancer, for a person who is exposed to estrogen is more than nine times that of a person who is not exposed to estrogen
Statistical Analysis Software (SAS) version 9.1 was chosen for the purpose of taking the parameter estimates and the design matrix of the conditional logistic regression model, which should be assessed
Summary
According to previous studies (Schlesselman,1982; Collett, 2003), logistic models have been extensively used in the field of medicine, and mainly applied in matched case control studies. These studies are known as retrospective studies, where individuals with a particular condition or disease (the case) are selected for comparison with a series of individuals in whom the condition or disease is absent (the control). Cases and controls are matched on the basis of confounding variables to control the effect of the confounding variables and this enables increase in efficiency. Matching is generally done on the basis of particular confounding variables such as age and ethnic group. In many real world situations, case control studies are used to investigate a combination of factors causing many diseases
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