Document Type : Research Paper
Abstract
This paper introduces the importance of comparative approaches in social research methods that are less known in the social sciences. The Decision tree is the one of the newest and most flexible analysis method for analyzing a large collection exploratory data analysis, Classification tree and interpretation of data through binary division. CART software; present a nonparametric analysis strategy to Homogeneous and non-homogenous, high risk and low risk subgroups for social researchers. Exploring the differences and similarities between social groups, and eventually predict their status in social planning is the most important application of this method. Clarifying the subject, in this paper, social demands of women in the four member countries of OIS (Turkey, Egypt, Saudi Arabia and Malaysia) as ideal types of each subgroup are analyzed by this software.
Keywords
- طالبان، محمدرضا، (1388). درآمدیروششناسانهبرتحلیلبولیفورانازانقلابایران، فصلنامه علوم اجتماعی، شماره 42، 43.
- کوثری، مسعود، (1386). تحلیلمقایسه‌ایکیفیدرعلوماجتماعی، نامه علوم اجتماعی، شماره 31.
- محمدی، نعیما. (1393). بررسی موردی مطالبات زنان در کشورهای ترکیه، مصر، عربستان سعودی و مالزی. فصلنامه مطالعات سیاسی جهان اسلام. دوره 4، شماره 12.
- محمدی، نعیما. (1392). بررسی جامعه شناختی جنبش‌های اجتماعی زنان در کشورهای عضو کنفرانس اسلامی. رساله دوره دکتری، رشته جامعه شناسی سیاسی. دانشگاه تربیت مدرس.
- Banerjee M, Biswas D, Sakr W and Wood D. (2000). Recursive partitioning for prognostic grouping of patients with clinically localized prostate carcinoma. American Cancer Society, 89: 404-411.
- Breiman L, Friedman J.H., OlShen R. A. and Ston C. J. (1984). Classification and Regression Trees. California, A Division of Wadsworth Inc.
- Callaghan F. (2008). Classification trees for survival data with competing risk. [dissertation], Doctor of philosophy, University of Pitters burgh,
- Cappelli C, D'Elia A. (2006). A tree-based method for selection of variables in models for ordinal data, Quaderni di Statistica, 8: 125-135.
- Dean L.S. (2007). A Method for detecting optimal splits over time in survival analysis using. tree-structured models. [dissertation], Doctor of philosophy, University of Pitters.burgh.
- Garzotto M, Beer T, Hodson R, Peters L, Hsieh Y, Barrera E,Klien T,Mori M. (2005). Improved detection of prostate cancer using classification and regression tree analysis, Clinical Oncology; 23 (19): 4322-4329.
- Gimotty P, Elder D, Fraker D, Botbyl J,Seller K, Elenitsas R, Ming M E, Schuchter, L, Spitz F R,Czerniecki B J,Guerry D. (2007). Identification of high-risk patients among those diagnosed with thin cutaneous melanomas, Clinical Oncology; 25(9): 1129-1134.
- Hess K R, Abbruzzese M C, Lenzi R, Raber M N, Abbruzzese J L. (1999). Classification and regression tree analysis 0f 1000 consecutive patients with unknown primary carcinoma. Clinical Cancer Research; 5: 3403-3410.
- Hothorn T, Hornik K, Zeileis A. (2008). Unbiased recursive partitioning: A Conditional inference framework. Journal of Computational and Graphical Statistics, 15(3): 651-674.
- Hothorn T, Hornik K, Zeileis A. (2006). Unbiased Recursive Partitioning: A Conditional Inference Framework. Computational and Graphical statistics; 15(3):651-674.
- Kantardzic M (2003).Data Mining: Concept, Model, Method and Algorithms. Wiley, Inter science.
- Lamborn K. Chang S and Prados M. (2004). Prognostic factors for survival of patients with glioblastoma: Recursive partitioning analysis. Nerro_Oncology; 6: 227-235.
- Liu J, Letaief K, Coa Z et al. (2004). A Reduced- complexity maximum-likelihood method for Multiuser detection, IEEE Transaction on Communication, 25(2):289-295.
- Molinaro A, Dudoit S, Van der Laan M. (2004). Tree-based multivariate regression and density estimation with right-censored data. Multivariate Analysis, 90: 154-177.
- Oberc M. (1993). Tree-structured methods for the proportional hazards model. [dissertation], Doctor of philosophy, University of Toronto,
- Schittgen R. (1999). Regression trees for survival Data-an approach to select Discontinuous split points by rank statistics Biometrical Journal; 41: 943-954.
- Segal M. (1988). Regression trees for Censored data. Biometrics,44: 35-48.
- Takashi O, Cook E.F, NakaMura T,Saito J, Ikawa F, Fukui T. (2006). Risk stratification for in-hospital mortality in spontaneous intra cerebral haemorrhage: A Classification and Regression Tree analysis. QJ Med,99: 743-750.
- Wang J. (2002). Tree-structured classification for multivariate binary responses. [Dissertation], Doctor of philosophy, North Carolina State University.
- Wernecke K, Possinger K, Kalb G and Stein J. Validating classification
- WU Y, Genton M, Stefanski L. (2009). A Comparison of Node-Splitting Rules in Recursive Partitioning Analysis of Multivariate Quantitative Structure Activity Data. Statistics in Biopharmaceutical Research, 1(2): 119-130.
)