方法对比
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| Demographic and Health Survey Analysis× | Living Standards Measurement Study× | |
|---|---|---|
| 领域 | Development Studies | Development Studies |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1984 | 1980 |
| 提出者≠ | USAID / The DHS Program (ICF) | World Bank (Living Standards Measurement Study programme) |
| 类型≠ | Nationally representative population and health survey | Multi-topic integrated household survey |
| 开创性文献≠ | Croft, T. N., Marshall, A. M. J., Allen, C. K., et al. (2018). Guide to DHS Statistics: DHS-7. Rockville, MD: ICF, The DHS Program. link ↗ | Grosh, M., & Glewwe, P. (Eds.). (2000). Designing Household Survey Questionnaires for Developing Countries: Lessons from 15 Years of the Living Standards Measurement Study. Washington, DC: World Bank. ISBN: 9780821345283 |
| 别名≠ | DHS, Demographic and Health Survey, DHS Program survey, Standard DHS | LSMS, LSMS Survey, Living Standards Survey, Integrated Household Survey |
| 相关 | 4 | 4 |
| 摘要≠ | The Demographic and Health Surveys (DHS) are nationally representative household surveys that provide standardised, internationally comparable data on population, health, and nutrition in low- and middle-income countries. Funded primarily by USAID and implemented through The DHS Program, they use model questionnaires, a complex multi-stage sample design, and a standardised wealth index to produce indicators of fertility, child and maternal mortality, family planning, child nutrition, and disease prevalence that drive health policy and programme monitoring worldwide. | The Living Standards Measurement Study (LSMS) is a multi-topic integrated household survey programme launched by the World Bank in 1980 to improve the quality of household data for measuring and analysing welfare in developing countries. Built around a modular questionnaire that links a detailed household interview to community and price questionnaires, the LSMS measures living standards through consumption expenditure rather than income, and connects welfare outcomes to their determinants — employment, education, health, agriculture, and access to services — within a single, internally consistent dataset. |
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