Multivariable Model-Building: A Pragmatic Approach to Regression Analysis based on Fractional Polynomials for Modelling Continuous Variables

By Patrick Royston, Willi Sauerbrei. 2008

865 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0fb7c1f96c92e08b84b0433cea53998489ce07bf

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Citations in the corpus

Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration (2012, methodology): “More extensive discussions of statistical analysis methods for binary outcome and for survival data can be found elsewhere [73,99-111].”
Association between the number of eggs and live birth in IVF treatment: an analysis of 400 135 treatment cycles. (2011, methodology): “We used the closed test procedure for function selection as described by Royston and Sauerbrei (2008).”
Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research (2013, methodology): “To enhance the reliability of future models, studies should be sufficiently large and based on a study protocol including a statistical analysis plan,including careful attention to the handling of missing data and continuous predictors (recommendation 13) [5,27,67].”
Cross-Validation, Shrinkage and Variable Selection in Linear Regression Revisited (2013, background): “For a more detailed discussion see chapter 2 of [8].”
Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects (2021, background): “Another alternative is the use of fractional polynomials (Nikolaeva et al., 2015; Royston & Sauerbrei, 2008; Sauerbrei et al., 2006), but this strategy was not applied in any of the reviewed articles.”
External validation of a Cox prognostic model: principles and methods (2013, methodology): “For example, sparsely populated categories may be combined, and ordinal variables may be coded so as to respect the ordering (see Reference [19], 55–56).”
Multiple imputation using chained equations: Issues and guidance for practice (2011, methodology): “We use a quadratic analysis model of sat96 on sat94 and its square, sat94sq (although a more appropriate choice might be a fractional polynomial model [33]).”
Towards better clinical prediction models: seven steps for development and an ABCD for validation. (2014, background): “Such shapes can efficiently be modelled using restricted cubic splines(2) or fractional polynomials.(17) These functions provide flexibility but use only few extra regression coefficients.”