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Article summary:

1. The paper introduces an algorithm that automates the process of purposeful selection of covariates in logistic regression.

2. A simulation study is conducted to compare the performance of this algorithm with three well-documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE.

3. The advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction, as it has the capability of retaining important confounding variables.

Article analysis:

The article provides a detailed overview of an algorithm for purposeful selection of covariates in logistic regression, as well as a comparison between its performance and that of three other variable selection procedures in SAS PROC LOGISTIC. The authors provide evidence from a simulation study to support their claims, which adds to the trustworthiness and reliability of the article. However, there are some potential biases that should be noted. For example, the authors do not explore any counterarguments or present both sides equally; they only focus on presenting their own argument for why their proposed algorithm is superior to other methods. Additionally, there is no discussion about possible risks associated with using this algorithm or any potential drawbacks that could arise from its use. Furthermore, while the authors provide evidence from a simulation study to support their claims, they do not provide any real-world examples or case studies to further illustrate how effective their proposed method is in practice. Finally, there is some promotional content throughout the article which could be seen as biased towards promoting their own method over others.