J S Witte1, S Greenland. 1. Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, OH 44109-1998, USA.
Abstract
PURPOSE: Conventional dose-response and trend analysis fits either a linear or categorical logistic model and tests the resulting coefficients. These analyses, however, are based on implausible assumptions. METHODS: We present an alternative approach that uses likelihood ratio tests to compare nested regression models and determine when a model is rich enough to capture the data trends. RESULTS: For illustration, we apply this approach to data on diet and colorectal polyps. CONCLUSIONS: Comparison of linear and quadratic spline logistic models indicates that the conventional approach of using only a linear logistic model would not appropriately describe the association between intake of fruits and vegetables and colorectal polyps in our data. Graphical checking further supports this conclusion.
PURPOSE: Conventional dose-response and trend analysis fits either a linear or categorical logistic model and tests the resulting coefficients. These analyses, however, are based on implausible assumptions. METHODS: We present an alternative approach that uses likelihood ratio tests to compare nested regression models and determine when a model is rich enough to capture the data trends. RESULTS: For illustration, we apply this approach to data on diet and colorectal polyps. CONCLUSIONS: Comparison of linear and quadratic spline logistic models indicates that the conventional approach of using only a linear logistic model would not appropriately describe the association between intake of fruits and vegetables and colorectal polyps in our data. Graphical checking further supports this conclusion.
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