The design of simulation studies in medical statistics by Andrea Burton, Douglas G. Altman, Patrick Royston and Roger L. Holder, Statistics in Medicine 2006; 25:4279-4292.

Author's response to reviews Title: Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study Authors:

Dichotomizing continuous predictors in multiple regression: a bad idea.

In medical research, continuous variables are often converted into categorical variables by grouping values into two or more categories. We consider in detail issues pertaining to creating just two groups, a common approach in clinical research. We argue that the simplicity achieved is gained at a cost; dichotomization may create rather than avoid problems, notably a considerable loss of power ...

Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

BACKGROUND Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one ...

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

BACKGROUND There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. METHODS Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Mu...

Reporting recommendations for tumor marker prognostic studies.

Lisa M. McShane, Biometric Research Branch, National Cancer Institute, Bethesda, MD Douglas G. Altman, Medical Statistics Group, Cancer Research UK, Centre for Statistics in Medicine, Wolfson College, Oxford, UK Willi Sauerbrei, Institut fuer Medizinische Biometrie und Medizinische Informatik, Universitaetsklinikum Freiburg, Freiburg, Germany Sheila E. Taube, Cancer Diagonisis Program, National...