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Citation Indices from GS

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:: Volume 25, Issue 2 (3-2015) ::
مجله‌ی بررسی‌ها 2015, 25(2): 175-190 Back to browse issues page
Sample Size Determination in Multilevel Models with Bayesian Approach
Omid Akhgari , Mousa Golalizadeh *
Abstract:   (4676 Views)

One of the most influential factors for each experimental research in various disciplines is to determine the sample size for the study. In statistical literature, the optimal sample size determination is depended on statistical power, confidence coefficient, effect size and cost function. Over all of these quantities, the special feature of the data under investigation has also has great impact on the sample size. If the data have intra-class correlation structure then the multilevel models are appropriate to analysis such data. In the present paper, we use three Bayesian performance criteria related to model parameters to determine the optimal sample size. Since the posterior distributions do not have closed forms, we should (and did) employ computational algorithms. However, the full conditional distributions of parameters had closed form, so to evaluate the performance of the relevant criterion the Gibbs sampling algorithm was performed to simulate the full conditional distributions of the model parameters. 

Keywords: Multilevel models, optimal sample size determination, bayesian performance criteria, design effect, sampling, Gibbs algorithm
Full-Text [PDF 194 kb]   (1392 Downloads)    
Type of Study: Research | Subject: General
Received: 2014/12/24 | Accepted: 2015/09/15 | Published: 2016/01/11
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Akhgari O, Golalizadeh M. Sample Size Determination in Multilevel Models with Bayesian Approach. مجله‌ی بررسی‌ها 2015; 25 (2) :175-190
URL: http://ijoss.srtc.ac.ir/article-1-85-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 25, Issue 2 (3-2015) Back to browse issues page
مجله‌ی بررسی‌های آمار رسمی ایران Ijoss Iranian Journal of Official Statistics Studies
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