Response to letter to the editor: “comment on unplanned out-of-hospital birth and risk factors of adverse perinatal outcome: findings from a prospective cohort”

Springer Science and Business Media LLC - Tập 27 - Trang 1-2 - 2019
François Javaudin1,2, Arnaud Legrand3, Philippe Pes1, Emmanuel Montassier1,2, Christelle Volteau3
1Department of Emergency Medicine, CHU Nantes, Nantes, France
2MiHAR Lab, Université de Nantes, Nantes, France
3DRCI, CHU Nantes, Nantes, France

Tóm tắt

The aim of this Letter to the Editor was to respond to a comment highlighting potential statistical biases in an analysis of our recently published article. We therefore specified the method for selecting the model variables in order to limit overfitting, then we used the Firth method to control the sparse data bias, and finally for checking internal validity we used bootstrapping methods. In total, the conclusions of our model were not changed by these new analyses.

Tài liệu tham khảo

Bidhendi Yarandi R, Panahi MH. Comment on unplanned out-of-hospital birth and risk factors of adverse perinatal outcome: findings from a prospective cohort. Scand J Trauma Resusc Emerg Med. 2019;27(1):37. Javaudin F, Hamel V, Legrand A, Goddet S, Templier F, Potiron C, et al. Unplanned out-of-hospital birth and risk factors of adverse perinatal outcome: findings from a prospective cohort. Scand J Trauma Resusc Emerg Med. 2019;27(1):26. Greenland S, Mansournia MA, Altman DG. Sparse data bias: a problem hiding in plain sight. BMJ. 2016;352:i1981. Firth D. Recent developments in quasi-likelihood methods. Bull Int Stat Inst. 1993;55:341–58. Steyerberg EW. Clinical prediction models: a practical approach to development, validation, and updating: Springer Science & Business Media; 2008.