Implementation of generalized linear model in Python

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Author: Chen-Xi LUO Qing-Yu ZHANG Xiang-Ying LI Pei-Zheng LI Jing WANG  Lu MA

Affiliation: School of Public Health, Wuhan University, Wuhan 430071, China

Keywords: Python SAS R Generalized linear model Statistical analysis

DOI: 10.12173/j.issn.1004-4337.202302030

Reference: Luo CX, Zhang QY, Li XY, Li PZ, Wang J, Ma L. Implementation of generalized linear model in Python[J]. Journal of Mathematical Medicine, 2023, 36(3): 161-165. DOI: 10.12173/j.issn.1004-4337.202302030[Article in Chinese]  Copied

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Abstract

Objective To explore the implementation method of generalized linear model in Python software, and compare its process and results with other common statistical software.

Method Using GLM function, Logit and Poisson function in statsmodles library of Python software, GLM function in R software and PROC GENMOD procedure step of SAS, the binomial distribution and Poisson distribution data sets were analyzed, and the process and analysis results of the three software algorithms were compared.

Results The logic of the three kinds of software to construct the generalized linear model is similar, but the software is slightly different in code implementation, model fitting methods and other aspects, and the results of the software are basically the same.

Conclusion Python softwares can use different algorithms to build generalized linear models, and can provide the same statistical analysis conclusions as other mainstream statistical softwares.

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References

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