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Statistical primer: an introduction to the application of linear mixed-effects models in cardiothoracic surgery outcomes research—a case study using homograft pulmonary valve replacement data.
- Source :
-
European Journal of Cardio-Thoracic Surgery . Oct2022, Vol. 62 Issue 4, p1-10. 10p. - Publication Year :
- 2022
-
Abstract
- Open in new tab Download slide OBJECTIVES The emergence of big cardio-thoracic surgery datasets that include not only short-term and long-term discrete outcomes but also repeated measurements over time offers the opportunity to apply more advanced modelling of outcomes. This article presents a detailed introduction to developing and interpreting linear mixed-effects models for repeated measurements in the setting of cardiothoracic surgery outcomes research. METHODS A retrospective dataset containing serial echocardiographic measurements in patients undergoing surgical pulmonary valve replacement from 1986 to 2017 in Erasmus MC was used to illustrate the steps of developing a linear mixed-effects model for clinician researchers. RESULTS Essential aspects of constructing the model are illustrated with the dataset including theories of linear mixed-effects models, missing values, collinearity, interaction, nonlinearity, model specification, results interpretation and assumptions evaluation. A comparison between linear regression models and linear mixed-effects models is done to elaborate on the strengths of linear mixed-effects models. An R script is provided for the implementation of the linear mixed-effects model. CONCLUSIONS Linear mixed-effects models can provide evolutional details of repeated measurements and give more valid estimates compared to linear regression models in the setting of cardio-thoracic surgery outcomes research. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10107940
- Volume :
- 62
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- European Journal of Cardio-Thoracic Surgery
- Publication Type :
- Academic Journal
- Accession number :
- 159478608
- Full Text :
- https://doi.org/10.1093/ejcts/ezac429