Household Sample Surveys in Developing and Transition Countries
Household Sample Surveys in Developing and Transition Countries
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发展中国家和转型国家的家庭抽样调查
DOI：
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发表时间：
2005
期刊：
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通讯作者：
Sistemas Integrales Santiago
中科院分区：
文献类型：
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作者：
Sistemas Integrales Santiago
在调查分析中需要考虑到调查数据是从采用复杂抽样设计选定的单位中获得的这一事实：在分析调查数据时需要使用加权数，在计算调查估计数的方差时需要反映复杂抽样设计。本章概述了权重的发展及其在计算调查估计数中的使用，并对调查数据的方差估计进行了一般性讨论。它首先涉及所谓的描述性估计，例如调查报告中广泛使用的总数、平均数和比例。然后，它讨论了三种形式的调查数据的分析方法，可以用来检查调查变量之间的关系，即多元线性回归模型，逻辑回归模型和多层次模型。这些模型构成了一套有价值的工具，可用于分析关键反应变量与若干其他因素之间的关系。在本章中，我们给出的例子来说明这些建模技术的使用，并提供指导的结果的解释。关键词：复杂的调查设计，分析统计，回归，逻辑回归，层次结构，多层次模型。发展中国家和转型期国家住户抽样调查
The fact that survey data are obtained from units selected with complex sample designs needs to be taken into account in the survey analysis: weights need to be used in analysing survey data and variances of survey estimates need to be computed in a manner that reflects the complex sample design. The present chapter outlines the development of weights and their use in computing survey estimates and provides a general discussion of variance estimation for survey data. It deals first with what are termed descriptive estimates, such as the totals, means and proportions that are widely used in survey reports. It then discusses three forms of analytic approaches to survey data that can be used to examine relationships between survey variables, namely, multiple linear regression models, logistic regression models and multilevel models. These models form a set of valuable tools for analysing the relationships between a key response variable and a number of other factors. In this chapter, we give examples to illustrate the use of these modelling techniques and also provide guidance on the interpretation of the results. Key terms: complex survey design, analytic statistics, regression, logistic regression, hierarchical structures, multilevel modelling. Household Sample Surveys in Developing and Transition Countries