Author(s)

Kaizhi Lu

Corresponding Author

Kaizhi Lu

ABSTRACT

Nowadays statistical tools have become an indispensable part in biomedical studies. Logistic regression, a model describing and estimating the relationship between one dependent variable and one or more independent variables, is one of the most widely used statistical analyses in multivariable models in medical research. Researchers need to be fully aware of the function of research designs applied, the applicability of statistical tests used, and the validity of the conclusions drawn. However, due to little time devoted in statistical training, researchers in epidemiology are short of the ability in system analysis and mathematical reasoning. This could result in generating avoidable statistical mistakes and compromising the final finding. So, a corresponding review and analysis of the logistic regression is in need. This article provides a walkthrough for creating logistic regression model within the context of medical study. It starts with the introduction of the model’s definition and follows by the discussion of operation and caution in each step of its application including variable selection, model building, model validation, and output interpretation.

KEYWORDS

Logistic regression, variable selection, model building, model validation, output interpretation, biostatistics