Journal
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
Volume 69, Issue 1, Pages 89-108Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00949650108812083
Keywords
nonlinearity; regression modelling; fractional polynomial; type I error
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Royston and Altman have demonstrated the usefulness of fractional polynomials in regression modelling, and have suggested model selection procedures for choosing appropriate fractional polynomial transformations. We investigate the performance of these procedures with particular regard to overfitting. We find the Type I error rates to be considerably in excess of their nominal value. We propose improvements which we show by simulation work reasonably well. We conclude that with the modifications, chi (2) or F approximations to likelihood ratio statistics to compare fractional polynomial models are adequate for practical purposes.
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