Multiple Indicator Cluster Survey 2021 - Fiji

Abstract
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Since its inception in the mid-1990s, the Multiple Indicator Cluster Surveys programme, known as MICS, has become the largest source of statistically sound and internationally comparable data on children and women worldwide. In countries as diverse as Bangladesh, Thailand, Fiji, Qatar, Cote d’Ivoire, Turkmenistan and Argentina, trained fieldwork teams conduct face-to-face interviews with household members on a variety of topics – focusing mainly on those issues that directly affect the lives of children and women. MICS is an integral part of plans and policies of many governments around the world, and a major data source for more than 30 Sustainable Development Goals (SDGs) indicators. The MICS programme continues to evolve with new methodologies and initiatives, including MICS Plus, MICS Link, MICS GIS and the MICS Tabulator.

Geographic coverage
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Fiji
The majority of MICS surveys are designed to be representative at the national level. Sample sizes are sufficient to generate robust data at the regional or provincial levels, and for urban and rural areas. Subnational surveys, covering specific population groups (such as Palestinians in Lebanon) or specific geographical areas (such as selected regions of East in Afghanistan) within countries are also conducted.

Analysis unit
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Household, Individual

Sampling procedure
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Sample sizes vary greatly from one survey to the other, currently averaging around 12,000 households (for national surveys).

The sample for the Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for areas of residence, and for geographical locations, such as regions, governorates, or districts. A multi-stage, stratified cluster sampling approach was typickly used for the selection of the survey sample. MICS6 surveys are not self-weighting. For reporting national level results, sample weights were used. A more detailed description of the sample design can be found in Appendix A of Final Report.

Mode of data collection
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Face-to-face [f2f]

{'Abstract': '自20世纪90年代中期问世以来，多项指标群组调查计划（简称MICS）已成为全球儿童和妇女统计数据可靠且具有国际可比性的最大来源。在孟加拉国、泰国、斐济、卡塔尔、科特迪瓦、土库曼斯坦和阿根廷等多样化的国家，经过培训的实地调查团队对家庭成员进行面对面访谈，涉及诸多主题——主要关注直接影响儿童和妇女生活的各类问题。MICS已成为众多国家规划和政策的有机组成部分，并且是超过30项可持续发展目标（SDGs）指标的主要数据来源。MICS计划持续演进，引入了新的方法和倡议，包括MICS Plus、MICS Link、MICS GIS以及MICS Tabulator等。', 'Geographic coverage': '地理覆盖范围', 'Fiji': '斐济', 'The majority of MICS surveys are designed to be representative at the national level. Sample sizes are sufficient to generate robust data at the regional or provincial levels, and for urban and rural areas. Subnational surveys, covering specific population groups (such as Palestinians in Lebanon) or specific geographical areas (such as selected regions of East in Afghanistan) within countries are also conducted.': '大多数MICS调查旨在在国家层面具有代表性。样本量足以在地区或省级水平以及城市和农村地区生成稳健的数据。此外，还进行覆盖特定人口群体（如黎巴嫩巴勒斯坦人）或特定地理区域（如阿富汗东部选定的地区）的次国家调查。', 'Analysis unit': '分析单元', 'Household, Individual': '家庭，个人', 'Sampling procedure': '抽样程序', 'Sample sizes vary greatly from one survey to the other, currently averaging around 12,000 households (for national surveys)': '各次调查的样本量差异很大，目前平均约为12,000户（针对国家调查）。', 'The sample for the Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for areas of residence, and for geographical locations, such as regions, governorates, or districts. A multi-stage, stratified cluster sampling approach was typickly used for the selection of the survey sample. MICS6 surveys are not self-weighting. For reporting national level results, sample weights were used. A more detailed description of the sample design can be found in Appendix A of Final Report.': '多项指标群组调查（MICS）的样本设计旨在为国家层面、居住区域以及诸如地区、省或区等地理位置提供大量指标关于儿童和妇女状况的估计。通常采用多阶段、分层聚类抽样方法来选择调查样本。MICS6调查不具有自加权特性。在报告国家层面结果时，使用了样本权重。关于样本设计的更详细描述可参见最终报告附录A。', 'Mode of data collection': '数据收集方式', 'Face-to-face [f2f]': '面对面 [f2f]'}