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:: Volume 10, Issue 3 (Autumn 2015) ::
2015, 10(3): 39-46 Back to browse issues page
Comparison of the results of Multivariate Finite Mixture Model with Factor and Cluster Analysis Methods in Dietary Pattern Identification
Z Razzaghi, Y Mehrabi , F Zayeri, A Rashidi, B Aghapoor
Abstract:   (4248 Views)
Background and Objectives: Today nutritionists use dietary pattern to find out the effect of food in health. Most common statistical methods to determine dietary pattern are factor analysis and cluster analysis.Mixture models are a combination of k probability distribution with different probability and provide a parametric model for unknown distributional shapes. Recently mixture model as the third method is used to determine dietary pattern. Then we compared this new method with other two methods available for this purpose. Materials & Methods: We analyzed data from 25 food groups of 400 high school girls in Ahar (Rashidi’s data), and compared the results of factor analysis, cluster analysis and multivariate normal mixture model for dietary pattern. Selection of the best mixture model was done by AIC and BIC criteria. Results: Three, two and five dietary pattern were obtained from factor analysis, cluster analysis and normal mixture model, respectively. Prevalence of these dietary patterns in normal mixture model was 6%,12%,34%,28%, and 20%, respectively. Conclusion: It is concluded that mixture model has two advantages over the two other methods. First, the proportion of each pattern in population is known and secondly, the average of consumption of each food group gets clear so more information can be obtained compared to the usual methods. Keywords: Mixture model, Factor analysis, Cluster analysis, Dietary pattern
Keywords: Mixture model, Factor analysis, Cluster analysis, Dietary pattern
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Type of Study: Research | Subject: nutrition
Received: 2014/05/1 | Accepted: 2015/09/7 | Published: 2015/09/30
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Razzaghi Z, Mehrabi Y, Zayeri F, Rashidi A, Aghapoor B. Comparison of the results of Multivariate Finite Mixture Model with Factor and Cluster Analysis Methods in Dietary Pattern Identification. Iranian Journal of Nutrition Sciences & Food Technology. 2015; 10 (3) :39-46
URL: http://nsft.sbmu.ac.ir/article-1-1611-en.html


Volume 10, Issue 3 (Autumn 2015) Back to browse issues page
Iranian Journal of  Nutrition Sciences & Food  Technology
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