Improving the robustness of fractional polynomial models by preliminary covariate transformation: a pragmatic approach

DOI10.1016/j.csda.2006.05.006zbMath1162.62387OpenAlexW2108606586MaRDI QIDQ1020079

Patrick Royston, Willi Sauerbrei

Publication date: 29 May 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.05.006

zbMATH Keywords

robustnessinfluenceleveragefractional polynomialschange of originregression modelling

Mathematics Subject Classification ID

Robustness and adaptive procedures (parametric inference) (62F35) General nonlinear regression (62J02) Diagnostics, and linear inference and regression (62J20)

Related Items (5)

A novel fractional implicit polynomial approach for stable representation of complex shapes ⋮ Detection of influential points as a byproduct of resampling-based variable selection procedures ⋮ Use of pretransformation to cope with extreme values in important candidate features ⋮ Multivariable regression model building by using fractional polynomials: description of SAS, STATA and R programs ⋮ Detecting an interaction between treatment and a continuous covariate: a comparison of two approaches

Uses Software

• Stata

Cites Work

• Robust diagnostic regression analysis
• Fractional polynomial model selection procedures: investigation of type i error rate
• Assessing Influence in Regression Analysis with Censored Data
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