1. Levitt NS, Steyn K, Lambert EV, Reagon G, Lombard CJ, Fourie JM, et al. Modifiable risk factors for Type 2 diabetes mellitus in a peri-urban community in South Africa. Diabet Med. 1999; 16(11): 946-50.
2. Harris M. Definition and classification of diabetes mellitus and the new criteria for diagnosis. Diabetes Care. 2010; 33(Suppl 1): S62-S69.
3. Bergenstal R, Kendall D, Franz M, Rubenstein A. Management of type 2 diabetes: A systematic approach to meeting the standards of care Self-management education medical nutrition therapy and exercise. Endocrinology 4th edition Philadelphia: WB Saunders Company. 2000: 810-20.
4.Nakhodayi zade M, Raissi dehkardi F, Babolkhani E. Comparison healthy lifestyle compared to type 2 diabetes in Shohada hospital in the city of Khorramabad in 1387. 2nd International Congress of Metabolic Syndrom Obesety and Diabetes; 2010.
5.What is diabetes? Comprehensive base of Medical Information of Iran; 2014.
6. CHarles E, McCulloch. An introduction to generalized linear mixed models. Annual Conference on Applied Statistics in Agriculture, Biometrics Unit and Statistc Center; 1997.
7. Bates D. Fitting linear mixed models in R. R news. 2005; 5(1): 27-30.
8. Venables WN, Dichmont CM. GLMs, GAMs and GLMMs: an overview of theory for applications in fisheries research. Fish Res. 2004; 70(2): 319-37.
9. Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens MH, et al. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol Evol. 2009; 24(3): 127-35.
10. Booth JG, Hobert JP. Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm. J R Stat Soc Series B. 1999; 61(1): 265-85.
11. Agresti A, Kateri M. Categorical data analysis: Springer; 2011.
12. Jiang J. Linear and generalized linear mixed models and their applications: Springer Science and Business Media; 2007.
13. Zhu H-T, Lee S-Y. Analysis of generalized linear mixed models via a stochastic approximation algorithm with Markov chain Monte-Carlo method. Comput Stat. 2002; 12(2): 175-83.
14. Breslow NE, Clayton DG. Approximate inference in generalized linear mixed models. J Am Stat Assoc. 1993; 88(421): 9-25.
15. Gilani N, Kazemnejad A, Zayeri F, Yazdani J. Comparison of Marginal Logistic Model with Repeated Measures and Conditional Logistic Model in Risk Factors Affecting Hypertension. J Mazandaran Univ Med Sci. 2011; 21(82): 27-35.
16. Fitzmaurice GM, Laird NM, Ware JH. Generalized Linear Mixed Models. applied longitudinal analysis: USA: John Wiley and Sons; 2012.
17. Kelestimur F, Cetin M, Pasaoglu H, Coksevim B, Cetinkaya F, Unluhizarci K, et al. The prevalence and identification of risk factors for type 2 diabetes mellitus and impaired glucose tolerance in Kayseri, central Anatolia, Turkey. Acta Diabetol. 1999; 36(1-2): 85-91.
18.Vaghari G, Sedaghat S, Joshaghani H, Hosseini SA, Niknejhad F, Angize A, et al. The prevalence of type II diabetes and associated risk factors in adults aged 25 to 65 years in Golestan Province. J Res Nurs Midwifery. 2011; 7(1): 69-74.
19. Merati M, Feizei A, Bager Nejad M. Prevalence of high blood pressure and diabetes and risk factors associated with them, based on a large study of the general population- an application of multivariate logistic regression models. Health Syst Res. 2012; 8(2): 193-203.
20. Skronal DHS. Multilevel logistic regression. Stat Med. 2002; 3: 411-20.