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Virtual Seminar: 'PROGRESS in sample size calculations for clinical prediction model research'

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  • UserProfessor Richard Riley, Centre for Prognosis Research, School of Medicine, Keele University
  • ClockTuesday 08 December 2020, 14:00-15:00
  • HouseVirtual Seminar .

If you have a question about this talk, please contact Alison Quenault.

If you would like to join this virtual seminar, please email: for more information.

There is a growing demand to personalise treatment and healthcare for individuals based on their prognosis and/or predicted response to treatment. For this reason, prognosis and prediction research has never been more important. Sadly, empirical evidence has shown that prognosis and prediction studies are often poorly designed, badly analysed, and selectively reported. The Prognosis Research Strategy (PROGRESS) framework was established to help address such shortcomings. In this talk, I will describe the PROGRESS framework, and highlight latest methodology guidance for calculating the sample size required for developing and validating clinical prediction models.

In terms of sample size for model development, current “rules of thumb” are based on having at least 10 events per predictor variable, but I will describe a more scientific approach based on minimising expected overfitting and ensuring precise parameter estimation. In terms of sample size for model validation, I will introduce a new approach that targets precise estimation of key model performance measures. Real examples are used to illustrate the concepts. The talk is intended for a wide audience.

This talk is part of the MRC Biostatistics Unit Seminars series.

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