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含定性变量回归模型的比较研究 被引量:1

A comparative study of regression models with qualitative variables
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摘要 系统对含定性变量的回归模型进行比较研究,通过引入虚拟变量处理自变量含定性变量的回归问题与折线回归,探讨了处理因变量含定性变量的线性概率模型、Probit模型与Logistic模型的区别与联系,以便针对具体情况选择合适的模型,最后利用SPSS自带数据给出实例分析. This paper makes a comparative study of regression models with qualitative variables. By introducing virtual variables to deal with the regression problems of independent variables with qualitative variables and polyline regression,the differences and relations between linear probability model,Probit model and Logistic model for dealing with dependent variables with qualitative variables are discussed,so that readers can choose appropriate models for specific situations. Finally,an example is given by using SPSS data.
作者 王丙参 陈庆美 魏艳华 WANG Bingcan;CHEN Qingmei;WEI Yanhua(School of Statistics,Capital University of Economics and Business,Beijing 100070;School of Mathematics and Statistics,Tianshui Normal University,Tianshui Gansu 741001)
出处 《宁夏师范学院学报》 2019年第10期21-26,共6页 Journal of Ningxia Normal University
基金 国家自然科学研究基金(11561060)
关键词 定性变量 虚拟变量 回归分析 PROBIT模型 LOGISTIC模型 Qualitative variable Virtual variable Regression analysis Probit model Logistic model
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  • 1Cook R D. Detection of influential observation in linear regression [J]. Technometrics, 1977, 19: 15-18.
  • 2Cook R D. Influential observation in linear regression [J]. Journal of the American Statistical Asso- ciation, 1979, 74: 169-174.
  • 3Cook R D, Weisberg S. Characterizations of an empirical influence function for detecting influential cases in regression [J]. Technometrics, 1980, 22: 495-508.
  • 4Pregibon D. Logistic regression diagnostic [J]. The Annals of Statistics, 1981, 9(4): 705 724.
  • 5Landwehr J M, Pregibon D, Shoemaker A C. Graphical methods for assessing logistic regression models [J]. Journal of the American Statistical Association, 1984, 79(385): 61-71.
  • 6Sugata S R, Guria S. Diagnostics in logistic regression models [J]. Journal of the Korean Statistical Society, 2008, 37: 89-94.
  • 7Hosmer D W, Lemeshow S. Applied Logistic Regression [M]. New York: John Wiley, 2000: 145-186.
  • 8Rao C R, Toutenburg H. Linear Model and Generalizations [M]. Berlin: Springer, 2008: 322-324.
  • 9Sheather S J. A Modern Approach to Regression with R[M]. Berlin: Springer, 2009: 277-278. http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0- 387-09607-0?changeHeader.
  • 10陈平,徐若曦.Metropolis-Hastings自适应算法及其应用[J].系统工程理论与实践,2008,28(1):100-108. 被引量:30

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