户内人口匹配数据的误用与改进——兼与《高等教育扩张与教育机会平等》一文商榷

    摘要：户内人口匹配数据被广泛地应用于社会学、人口学及相关领域的研究中,但户内人口匹配数据的选择性偏差常常被研究者忽略。针对这类问题本文利用2000年第五次人口普查和2005年1%人口抽样调查原始抽样数据对户内父子、母子和夫妻关系进行匹配,发现三种匹配数据均存在不同程度的选择性偏差,体现在年龄、性别、流动状况、城乡分布、教育、地区分布等方面。在此基础上,本文对《高等教育扩张与教育机会不平等》一文的匹配数据、分析模型和研究结论进行再检验。发现匹配数据的选择性偏差对分析模型和研究结论的影响是确定的。户内人口匹配数据的偏差不仅影响统计模型因素判断程度的错误,甚至完全改变影响因素的作用方向。为了减小匹配数据偏差的影响,本文提出户内人口匹配数据偏差的调整方法和思路,认为加权和再抽样方法能够在一定程度上弥补选择性偏差,相比来说,加权模型的调整效果更加理想。
    关键词：户内匹配; 人口普查数据; 加权; 再抽样
     
    On the Misusage and Adjustment of Household Members Matched Data:A discussion with the paper Expansion of Higher Education and Inequality in Opportunity of Education
    Abstract:The data of household members matched are widely used in sociology，demography and related research，but the selection bias of the matched data is often ignored．This paper uses the raw data of the Fifth Census in 2000 and 1% Population Sample Survey in 2005 to match three kinds of relations，i． e． ，father and sons，mother and children，husband and wife，and confirms that the selection bias exist in these matched data grouped by age，gender，migration status，rural and urban distribution，education，geographical distribution，and so on． Based on the matched data，this paper re-tests the matched data，analysis models and conclusions of the paper Expansion of Higher Education and Inequality in Opportunity of Education and finds out that the selection bias of matched data would influence the accuracy of model analysis and research conclusion． For further reducing the impact of matched data bias，we propose two adjustment methods and find out that re-sampling and weighting
    methods can reduce the selective bias．
    全文阅读
    文章出处：社会学研究，2011年第3期