A procedure to tabulate and plot results after flexible modeling of a quantitative covariate
Nicola Orsini
Division of Nutritional Epidemiology
National Institute of Environmental Medicine
Karolinska Institutet
Stockholm, Sweden
[email protected]
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Sander Greenland
Departments of Epidemiology and Statistics
University of California–Los Angeles
Los Angeles, CA
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Abstract. The use of flexible models for the relationship between a quantitative
covariate and the response variable can be limited by the difficulty in interpreting
the regression coefficients. In this article, we present a new postestimation
command, xblc, that facilitates tabular and graphical presentation of these relationships.
Cubic splines are given special emphasis. We illustrate the command
through several worked examples using data from a large study of Swedish men
on the relation between physical activity and the occurrence of lower urinary tract
symptoms.
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Nicola Orsini, Sander Greenland
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xblc, cubic spline, modeling strategies, logistic regression
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