Coverage and flexibility : issues should be considered for analyzing by generalized linear model in health science research

Authors

  • Assoc. Prof. Dr. Pongdech Sarakarn Department of Epidemiology and Biostatistics, Faculty of Public Health, Khon Kaen University
  • Donlagon Jumparway 0836668805

Keywords:

general linear model, generalized linear model, link function

Abstract

Generalized linear model (GLMs) is the model which extends from the general linear model (GLM) for developing the predictive equations or linear relationship between outcome and covariates, which covers both continuous and discrete outcomes based on the distribution of exponential family by random component and link function. Furthermore, such model is continuously developed and extended as various models and methods which can be used in the complicated research as well, such as the generalized additive model (GAM) for smoothing relationship and generalized estimating equation (GEE) for correlated outcomes. Therefore, flexibility and coverage issues of the generalized linear model should be considered and brought to use in the process of data analysis for saving the time-consuming of learning on each statistical method of statistics and being convenient for using, especially in health science research.

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Published

2020-12-30

How to Cite

Sarakarn, P., & Jumparway, D. (2020). Coverage and flexibility : issues should be considered for analyzing by generalized linear model in health science research. Journal of Health Science and Community Public Health, 3(2), 144–158. retrieved from https://he01.tci-thaijo.org/index.php/jhscph/article/view/244276

Issue

Vol. 3 No. 2 (2020): July - December

Section

Literature Review Article

License

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