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Abstract Details
Activity Number:
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190
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #302273 |
Title:
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Comparing Splines and Fractional Polynomials in Modeling Time-to-Event Data
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Author(s):
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Leila D. Amorim*+ and NĂvea B. Silva
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Companies:
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Federal University of Bahia and Federal University of Minas Gerais
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Address:
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Rua Joaquim Ferraro do Nascimento, 102, apto.1003,, Salvador-Bahia, International, 41830-440, Brazil
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Keywords:
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splines ;
fractional polynomials ;
cox model ;
time-to-event data ;
survival analysis
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Abstract:
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Smoothing approaches have become increasily popular in applied research, particularly due to their flexibility to model the functional form of continuous covariate's effect on an outcome. Splines methods and fractional polynomials have extensively been used in various applications. Research has been conducted for evaluating the performance of such approaches on the fit of generalized linear models and Cox models. However, comparison between the smoothing approaches in the context of analyzing time-to-event data is still limited. We compared regression splines and smoothing splines, which are techniques that differ in the number of knots used, in the way of determining their positions and on how the parameters for the polynomial pieces are estimated, to the fractional polynomials. These approaches are applied to the analysis of diarrhea time-to-event data. Simulation studies examined the strengths and weakness of different smoothing approaches.
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