Volume 14, Issue 1 (Paramedical Sciences and Military Health (Spring 2019) 2019)                   Paramedical Sciences and Military Health 2019, 14(1): 33-38 | Back to browse issues page

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Fallahzadeh H, Asadi F. Generalized linear mixed models:Introduction,Estimation method and Application in medical studies. Paramedical Sciences and Military Health. 2019; 14 (1) :33-38
URL: http://jps.ajaums.ac.ir/article-1-176-en.html
1- Department of Biological Statistics, Faculty of Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
2- Department of Biological Statistics, Faculty of Para-medicine and Health, Birjand University of Medical Sciences, Birjand, Iran , fariba.asadi3@gmail.com
Abstract:   (504 Views)
Introduction: In medical studies, we are often confronted with data that have been collected longitudinal or cluster. The generalized Linear mixed models that had been developed from the generalized linear models and linear mixed models- are useful methods for analyzing such data. In this paper, we introduced this models and their estimation methodologies using examples of their application in the medical field.
Methods and Materials: The data of this study were related to 8525 lung cancer patients that mixed logistic regression model was used for the analysis with R software version 3.0.1 by Laplace method.
Results: Regression analysis showed that age, level of experience of doctors and cancer stage were factors affecting on recovery of patients. Individual and not measured factors covered 4.03 variation of response variable.
Conclusion: Generalized linear mixed models include a wide range of data, but many researchers ignored the random effects due to the lack of familiarity with these models. This mistakenly leads to some parameters have significant meanings. Correct use of these models leads to prevent many false results.
Full-Text [PDF 2189 kb]   (354 Downloads)    
Type of Study: Research | Subject: full articles
Received: 2019/06/8 | Published: 2019/05/31

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