five

Multiple Indicator Cluster Survey 2006 - Kazakhstan

收藏
nada-demo.ihsn.org2021-10-13 更新2025-03-23 收录
下载链接:
https://nada-demo.ihsn.org/index.php/catalog/98
下载链接
链接失效反馈
官方服务:
资源简介:
Abstract --------------------------- The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular. MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria. Survey Objectives The 2006 Kazakhstan Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Kazakhstan - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Kazakhstan and to strengthen technical expertise in the design, implementation, and analysis of such systems. Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire. Survey Implementation The survey was carried out by The Agency of Statistics of the Republic of Kazakhstan, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination. Geographic coverage --------------------------- The sample for the Kazakhstan 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 urban and rural areas, as well as at sub-national level for 16 regions - 14 Oblasts and 2 Cities: - Akmola Oblast - Aktobe Oblast - Almaty Oblast - Atyrau Oblast - West Kazakhstan Oblast - Zhambyl Oblast - Karaganda Oblast - Kostanai Oblast - Kyzylorda Oblast - Mangistau Oblast - South Kazakhstan Oblast - Pavlodar Oblast - North Kazakhstan Oblast - East Kazakhstan Oblast - Astana City - Almaty City Analysis unit --------------------------- Households (defined as a group of persons who usually live and eat together) De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household) Women aged 15-49 Children aged 0-4 Universe --------------------------- The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household. Kind of data --------------------------- Sample survey data [ssd] Sampling procedure --------------------------- Regions were identified as the main sampling domains and the sample was selected in two stages. The sample was stratified by urban and rural areas (which represent second level territorial and administrative units). 1999 Population Census enumeration areas were selected as Primary Sampling Units (PSUs). The number of primary sampling units (PSUs) for oblast and main cities depended on the total population at the beginning of 2005. At the first stage, mentioned number of PSUs was randomly selected for each stratum. In general, 625 PSUs were selected within the country. At the second stage, 24 households were systematically selected in each sampled primary sampling unit. Thus, total number of sampled households made 15,000. The sample was stratified by region and is not self-weighting. For reporting national level results, sample weights are used. For more information on the sampling design please see the sampling design document under the technical documents folder. Sampling deviation --------------------------- No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates. Mode of data collection --------------------------- Face-to-face [f2f] Research instrument --------------------------- The questionnaires for the Kazakhstan MICS were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. The household questionnaire includes household characteristics, education, child labour, water and sanitation, and salt iodization, with optional modules for child discipline, maternal mortality and durability of housing and Kazakhstan specific modules about UICEF. In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child. The women's questionnaire include women's characteristics, child mortality, maternal and newborn health, marriage and union, contraception, and HIV/AIDS knowledge, with optional modules for domestic violence, and sexual (reproductive) behavior and Kazakhstan specific module for Tuberculosis. The children's questionnaire includes children's characteristics, birth registration and early learning, breastfeeding, care of illness, immunization, and anthropometry, with an optional module for child development. The questionnaires are based on the MICS3 model questionnaire; however, some Modules were adapted to Kazakhstan (in particular, Education Module, which was considerably changed). English questionnaires were translated into Russian and Kazakh. Questionnaires were pre-tested in Fabrichnyi (Almaty Oblast) and Kordai (Zhambyl Oblast) settlements in November 2005. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. All questionnaires and modules are provided as external resources. Cleaning operations --------------------------- Data editing took place at a number of stages throughout the processing (see Other processing), including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files Detailed documentation of the editing of data can be found in the data processing guidelines Response rate --------------------------- Of the 15,000 households selected for the sample, 14,984 were found to be occupied. Of these 14,564 were successfully interviewed for a household response rate of 97.2 percent. In the interviewed households, 14,719 women (age 15-49) were identified. Of these, 14,570 were successfully interviewed, yielding a response rate of 99.0 percent. In addition, 4,424 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 4,416, which correspond to a response rate of 99.8 percent. Overall response rates calculated for the interviews of women 15-49 years of age and children under-5 were 96.2 and 97.0 percents respectively. Household response rates in rural areas were higher than in urban - 99.4 and 95.6 percent respectively. Overall household response rate throughout the country was high and varied from 91.6 percent in Almaty City up to 99 percent in Zhambyl Oblast. Sampling error estimates --------------------------- Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2006 MICS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors can be evaluated statistically. The sample of respondents to the 2006 MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which is the square root of the variance. Confidence intervals are calculated for each statistic within which the true value for the population can be assumed to fall. Plus or minus two standard errors of the statistic is used for key statistics presented in MICS, equivalent to a 95 percent confidence interval. If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formulae for calculating sampling errors. However, the 2006 MICS sample is the result of a multi-stage stratified design, and consequently needs to use more complex formulae. The SPSS complex samples module has been used to calculate sampling errors for the 2006 MICS. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. This method is documented in the SPSS file CSDescriptives.pdf found under the Help, Algorithms options in SPSS. Sampling errors have been calculated for a select set of statistics (all of which are proportions due to the limitations of the Taylor linearization method) for the national sample, urban and rural areas, and for each of the five regions. For each statistic, the estimate, its standard error, the coefficient of variation (or relative error -- the ratio between the standard error and the estimate), the design effect, and the square root design effect (DEFT -- the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used), as well as the 95 percent confidence intervals (+/-2 standard errors). Details of the sampling errors are presented in the sampling errors appendix to the report and in the sampling errors table presented in te external resources. Data appraisal --------------------------- A series of data quality tables and graphs are available to review the quality of the data and include the following: Age distribution of the household population Age distribution of eligible women and interviewed women Age distribution of eligible children and children for whom the mother or caretaker was interviewed Age distribution of children under age 5 by 3 month groups Age and period ratios at boundaries of eligibility Percent of observations with missing information on selected variables Presence of mother inthe household and person interviewed for the under 5 questionnaire School attendance by single year age Sex ratio at birth among children ever born, surviving and dead by age of respondent Distribution of women by time since last birth Scatterplot of weight by height, weight by age and height by age Graph of male and female population by single years of age Population pyramid The results of each of these data quality tables is shown in the appendix of the final report and is also given in the external resources section. The general rule for presentation of missing data in the final report tabulations is that a column is presented for missing data if the percentage of cases with missing data is 1% or more. Cases with missing data on the background characteristics (e.g. education) are included in the tables, but the missing data rows are suppressed and noted at the bottom of the tables in the report (not in the SPSS output, however).

摘要 --------------------------- 联合国儿童基金会(UNICEF)开发的多指标聚类调查(MICS)是一项旨在帮助各国填补关于人类发展,尤其是儿童和妇女状况数据空白的家庭调查项目。MICS能够产生统计上可靠、国际上可比的社会指标估计。当前阶段的MICS专注于提供监测千年发展目标(MDGs)、世界儿童适宜环境(WFFC)以及其他重大国际承诺(如联合国大会特别会议(UNGASS)关于艾滋病和 Abuja 目标针对疟疾)的监测工具。 调查目标 2006年哈萨克斯坦多指标聚类调查的主要目标如下: - 提供最新信息,以评估哈萨克斯坦儿童和妇女的状况 - 提供数据,以监测实现千年宣言、世界儿童适宜环境(WFFC)目标以及其他国际公认目标(作为未来行动的基础) - 为改善哈萨克斯坦的数据和监测系统做出贡献,并加强在设计、实施和分析此类系统方面的技术专长。 调查内容 MICS问卷采用模块化设计,可轻松定制以满足国家的需求。它们包括家庭问卷、15-49岁妇女问卷以及5岁以下儿童问卷(由母亲或照顾者填写)。除了核心模块外,各国可以选择在每个问卷中包含哪些模块。 调查实施 该调查由哈萨克斯坦共和国统计局实施,并得到联合国儿童基金会和其他合作伙伴的支持和协助。通过一系列区域研讨会提供调查的技术协助和培训,涵盖问卷内容、抽样和调查实施;数据处理;数据质量和数据分析;报告撰写和传播。 地理覆盖范围 --------------------------- 哈萨克斯坦多指标聚类调查(MICS)的样本设计旨在在全国层面、城乡地区以及16个地区(14个州和2个城市)的次国家层面提供大量指标关于儿童和妇女状况的估计: - 阿克莫拉州 - 阿克托别州 - 阿拉木图州 - 阿特劳州 - 西哈萨克斯坦州 - 贾姆拜州 - 卡拉干达州 - 科斯套州 - 克孜勒奥尔达州 - 曼吉斯套州 - 南哈萨克斯坦州 - 帕夫洛达尔州 - 北哈萨克斯坦州 - 东哈萨克斯坦州 - 阿斯塔纳市 - 阿拉木图市 分析单元 --------------------------- 家庭(定义为通常生活在一起并共同进食的人群) 法定家庭成员(定义为通常居住在家庭中的人,可能包括前一天晚上没有在家庭中过夜的人,但不包括前一天晚上在家庭中过夜但不通常居住在家庭中的访客) 15-49岁妇女 0-4岁儿童 总体 --------------------------- 该调查涵盖了所有法定家庭成员(常住居民)、所有居住在家庭中的15-49岁妇女,以及所有居住在家庭中的0-4岁儿童(5岁以下)。 数据类型 --------------------------- 样本调查数据 [ssd] 抽样程序 --------------------------- 地区被确定为主要的抽样领域,样本在两个阶段进行选择。样本按城市和农村地区(代表第二级领土和行政单位)分层。1999年人口普查区被选为主要抽样单位(PSU)。州和主要城市的初级抽样单位(PSU)的数量取决于2005年初的总人口。 在第一阶段,为每个层随机选择了上述数量的PSU。通常,全国范围内选择了625个PSU。在第二阶段,在每个抽样初级抽样单位中系统地选择了24户家庭。因此,抽样家庭的总数为15,000户。 样本按地区分层,不具有自加权性。在报告国家层面结果时,使用样本权重。 有关抽样设计的更多信息,请参阅技术文件文件夹下的抽样设计文档。 抽样偏差 --------------------------- 未对原始样本设计做出重大调整。所有样本枚举区域均被访问并成功访谈,响应率良好。 数据收集方式 --------------------------- 面对面 [f2f] 研究工具 --------------------------- 哈萨克斯坦MICS的问卷是基于MICS3模型问卷的 structured questionnaires,经过一些修改和补充。每个家庭都进行了家庭问卷,收集了关于家庭成员的各种信息,包括性别、年龄、关系和孤儿状态。家庭问卷包括家庭特征、教育、儿童劳动、水和卫生以及食盐碘化,可选模块包括儿童纪律、孕产妇死亡和住房的耐用性以及哈萨克斯坦特定的UNICEF模块。 除了家庭问卷外,还为每个家庭中的15-49岁妇女和5岁以下儿童进行了问卷调查。对于儿童,问卷由孩子的母亲或照顾者填写。 妇女问卷包括妇女特征、儿童死亡率、孕产妇和新生儿健康、婚姻和联合、避孕和艾滋病知识,可选模块包括家庭暴力和性(生殖)行为以及哈萨克斯坦特定的结核病模块。 儿童问卷包括儿童特征、出生登记和早期学习、母乳喂养、疾病护理、免疫和人体测量学,可选模块包括儿童发展。 问卷基于MICS3模型问卷;然而,一些模块已根据哈萨克斯坦进行了调整(特别是教育模块,该模块发生了相当大的变化)。英语问卷翻译成俄语和哈萨克语。问卷于2005年11月在费布里奇尼(阿拉木图州)和科尔德伊(贾姆拜州)定居点进行了预测试。根据预测试的结果,对问卷的文字和翻译进行了修改。所有问卷和模块均作为外部资源提供。 数据清理 --------------------------- 在整个处理过程中进行了数据编辑,包括: a) 办公室编辑和编码 b) 数据录入期间 c) 结构检查和完整性 d) 次级编辑 e) SPSS数据文件的结构检查 有关数据编辑的详细文档可以在数据处理指南中找到。 响应率 --------------------------- 在选定的15,000户样本中,发现14,984户有人居住。其中14,564户被成功访谈,家庭响应率为97.2%。在受访的家庭中,确定了14,719名(15-49岁)妇女。其中,14,570名被成功访谈,响应率为99.0%。此外,家庭问卷中列出了4,424名5岁以下儿童。其中,完成了4,416份问卷,响应率为99.8%。总体而言,15-49岁妇女和5岁以下儿童的访谈响应率分别为96.2%和97.0%。 农村地区的家庭响应率高于城市地区 - 分别为99.4%和95.6%。全国范围内的总体家庭响应率很高,从阿拉木图市的91.6%到贾姆拜州的99%不等。 抽样误差估计 --------------------------- 样本调查的估计受到两种类型的误差的影响:1)非抽样误差和2)抽样误差。非抽样误差是数据收集和处理实施中的错误的结果。在2006年MICS的实施过程中,为最大限度地减少此类错误做出了许多努力,然而,非抽样误差是无法避免且难以进行统计分析的。 抽样误差可以统计评估。2006年MICS的受访者样本只是从同一人口中可能选择的大量样本之一,使用相同的设计和预期规模。每个这样的样本都会产生与实际样本选择的结果略有不同的结果。抽样误差是衡量所有可能样本之间调查结果差异的指标,尽管差异的程度并不完全清楚,但可以从调查结果中估计出来。抽样误差以特定统计量(平均值或百分比)的标准误差来衡量,这是方差的平方根。对于每个统计量,计算置信区间,其中可以假设人口的真实值落在此区间内。MICS中呈现的关键统计量的加减两个标准误差用于关键统计量,相当于95%的置信区间。 如果受访者样本是一个简单随机样本,就可以使用简单的公式来计算抽样误差。然而,2006年MICS样本是分层多阶段设计的产物,因此需要使用更复杂的公式。SPSS复杂样本模块已用于计算2006年MICS的抽样误差。该模块使用泰勒线性化方法对调查估计进行方差估计,这些估计是平均值或比例。该方法在SPSS文件CSDescriptives.pdf中有记录,该文件位于SPSS帮助、算法选项下。 已为选定的一组统计量(由于泰勒线性化方法的限制,所有这些统计量都是比例)计算了国家样本、城市和农村地区以及五个地区的抽样误差。对于每个统计量,估计值、其标准误差、变异系数(或相对误差 - 标准误差与估计值的比率)、设计效应以及平方根设计效应(DEFT - 使用给定样本设计计算的标准误差与如果使用简单随机样本将得到的标准误差之间的比率),以及95%的置信区间(加减两个标准误差)。 抽样误差的详细信息在报告的抽样误差附录中呈现,并在外部资源中的抽样误差表中呈现。 数据评估 --------------------------- 一系列数据质量表和图表可用于审查数据质量,包括以下内容: - 家庭人口年龄分布 - 合格妇女和受访妇女的年龄分布 - 合格儿童和母亲或照顾者访谈的儿童的年龄分布 - 5岁以下儿童按3个月年龄组的年龄分布 - 合格边界的年龄和时期比率 - 具有选定变量缺失信息的观测值的百分比 - 家庭中是否有母亲以及为5岁以下儿童问卷访谈的人 - 单一年龄学校的出席率 - 儿童出生时男性和女性的性别比例,按受访者年龄分组 - 按时间从上次分娩以来划分妇女 - 体重与身高、体重与年龄和身高与年龄的散点图 - 按单一年龄划分的男性和女性人口图 - 人口金字塔 每个数据质量表的结果均在最终报告的附录中呈现,并在外部资源部分给出。 最终报告中缺失数据的呈现规则是,如果缺失数据的案例百分比达到1%或更多,则呈现缺失数据的列。具有背景特征(例如教育)缺失数据的案例包括在表中,但缺失数据行被抑制,并在报告底部(而不是SPSS输出)注明。 数据清理 --------------------------- 在整个处理过程中进行了数据编辑,包括: a) 办公室编辑和编码 b) 数据录入期间 c) 结构检查和完整性 d) 次级编辑 e) SPSS数据文件的结构检查 有关数据编辑的详细文档可以在数据处理指南中找到。 响应率 --------------------------- 在选定的15,000户样本中,发现14,984户有人居住。其中14,564户被成功访谈,家庭响应率为97.2%。在受访的家庭中,确定了14,719名(15-49岁)妇女。其中,14,570名被成功访谈,响应率为99.0%。此外,家庭问卷中列出了4,424名5岁以下儿童。其中,完成了4,416份问卷,响应率为99.8%。总体而言,15-49岁妇女和5岁以下儿童的访谈响应率分别为96.2%和97.0%。 农村地区的家庭响应率高于城市地区 - 分别为99.4%和95.6%。全国范围内的总体家庭响应率很高,从阿拉木图市的91.6%到贾姆拜州的99%不等。 抽样误差估计 --------------------------- 样本调查的估计受到两种类型的误差的影响:1)非抽样误差和2)抽样误差。非抽样误差是数据收集和处理实施中的错误的结果。在2006年MICS的实施过程中,为最大限度地减少此类错误做出了许多努力,然而,非抽样误差是无法避免且难以进行统计分析的。 抽样误差可以统计评估。2006年MICS的受访者样本只是从同一人口中可能选择的大量样本之一,使用相同的设计和预期规模。每个这样的样本都会产生与实际样本选择的结果略有不同的结果。抽样误差是衡量所有可能样本之间调查结果差异的指标,尽管差异的程度并不完全清楚,但可以从调查结果中估计出来。抽样误差以特定统计量(平均值或百分比)的标准误差来衡量,这是方差的平方根。对于每个统计量,计算置信区间,其中可以假设人口的真实值落在此区间内。MICS中呈现的关键统计量的加减两个标准误差用于关键统计量,相当于95%的置信区间。 如果受访者样本是一个简单随机样本,就可以使用简单的公式来计算抽样误差。然而,2006年MICS样本是分层多阶段设计的产物,因此需要使用更复杂的公式。SPSS复杂样本模块已用于计算2006年MICS的抽样误差。该模块使用泰勒线性化方法对调查估计进行方差估计,这些估计是平均值或比例。该方法在SPSS文件CSDescriptives.pdf中有记录,该文件位于SPSS帮助、算法选项下。 已为选定的一组统计量(由于泰勒线性化方法的限制,所有这些统计量都是比例)计算了国家样本、城市和农村地区以及五个地区的抽样误差。对于每个统计量,估计值、其标准误差、变异系数(或相对误差 -- 标准误差与估计值的比率)、设计效应以及平方根设计效应(DEFT -- 使用给定样本设计计算的标准误差与如果使用简单随机样本将得到的标准误差之间的比率),以及95%的置信区间(加减两个标准误差)。 抽样误差的详细信息在报告的抽样误差附录中呈现,并在外部资源中的抽样误差表中呈现。 数据评估 --------------------------- 一系列数据质量表和图表可用于审查数据质量,包括以下内容: - 家庭人口年龄分布 - 合格妇女和受访妇女的年龄分布 - 合格儿童和母亲或照顾者访谈的儿童的年龄分布 - 5岁以下儿童按3个月年龄组的年龄分布 - 合格边界的年龄和时期比率 - 具有选定变量缺失信息的观测值的百分比 - 家庭中是否有母亲以及为5岁以下儿童问卷访谈的人 - 单一年龄学校的出席率 - 儿童出生时男性和女性的性别比例,按受访者年龄分组 - 按时间从上次分娩以来划分妇女 - 体重与身高、体重与年龄和身高与年龄的散点图 - 按单一年龄划分的男性和女性人口图 - 人口金字塔 每个数据质量表的结果均在最终报告的附录中呈现,并在外部资源部分给出。 缺失数据的呈现规则是,如果缺失数据的案例百分比达到1%或更多,则呈现缺失数据的列。具有背景特征(例如教育)缺失数据的案例包括在表中,但缺失数据行被抑制,并在报告底部(而不是SPSS输出)注明。 数据清理 --------------------------- 在整个处理过程中进行了数据编辑,包括: a) 办公室编辑和编码 b) 数据录入期间 c) 结构检查和完整性 d) 次级编辑 e) SPSS数据文件的结构检查 有关数据编辑的详细文档可以在数据处理指南中找到。 响应率 --------------------------- 在选定的15,000户样本中,发现14,984户有人居住。其中14,564户被成功访谈,家庭响应率为97.2%。在受访的家庭中,确定了14,719名(15-49岁)妇女。其中,14,570名被成功访谈,响应率为99.0%。此外,家庭问卷中列出了4,424名5岁以下儿童。其中,完成了4,416份问卷,响应率为99.8%。总体而言,15-49岁妇女和5岁以下儿童的访谈响应率分别为96.2%和97.0%。 农村地区的家庭响应率高于城市地区 - 分别为99.4%和95.6%。全国范围内的总体家庭响应率很高,从阿拉木图市的91.6%到贾姆拜州的99%不等。 抽样误差估计 --------------------------- 样本调查的估计受到两种类型的误差的影响:1)非抽样误差和2)抽样误差。非抽样误差是数据收集和处理实施中的错误的结果。在2006年MICS的实施过程中,为最大限度地减少此类错误做出了许多努力,然而,非抽样误差是无法避免且难以进行统计分析的。 抽样误差可以统计评估。2006年MICS的受访者样本只是从同一人口中可能选择的大量样本之一,使用相同的设计和预期规模。每个这样的样本都会产生与实际样本选择的结果略有不同的结果。抽样误差是衡量所有可能样本之间调查结果差异的指标,尽管差异的程度并不完全清楚,但可以从调查结果中估计出来。抽样误差以特定统计量(平均值或百分比)的标准误差来衡量,这是方差的平方根。对于每个统计量,计算置信区间,其中可以假设人口的真实值落在此区间内。MICS中呈现的关键统计量的加减两个标准误差用于关键统计量,相当于95%的置信区间。 如果受访者样本是一个简单随机样本,就可以使用简单的公式来计算抽样误差。然而,2006年MICS样本是分层多阶段设计的产物,因此需要使用更复杂的公式。SPSS复杂样本模块已用于计算2006年MICS的抽样误差。该模块使用泰勒线性化方法对调查估计进行方差估计,这些估计是平均值或比例。该方法在SPSS文件CSDescriptives.pdf中有记录,该文件位于SPSS帮助、算法选项下。 已为选定的一组统计量(由于泰勒线性化方法的限制,所有这些统计量都是比例)计算了国家样本、城市和农村地区以及五个地区的抽样误差。对于每个统计量,估计值、其标准误差、变异系数(或相对误差 -- 标准误差与估计值的比率)、设计效应以及平方根设计效应(DEFT -- 使用给定样本设计计算的标准误差与如果使用简单随机样本将得到的标准误差之间的比率),以及95%的置信区间(加减两个标准误差)。 抽样误差的详细信息在报告的抽样误差附录中呈现,并在外部资源中的抽样误差表中呈现。 数据评估 --------------------------- 一系列数据质量表和图表可用于审查数据质量,包括以下内容: - 家庭人口年龄分布 - 合格妇女和受访妇女的年龄分布 - 合格儿童和母亲或照顾者访谈的儿童的年龄分布 - 5岁以下儿童按3个月年龄组的年龄分布 - 合格边界的年龄和时期比率 - 具有选定变量缺失信息的观测值的百分比 - 家庭中是否有母亲以及为5岁以下儿童问卷访谈的人 - 单一年龄学校的出席率 - 儿童出生时男性和女性的性别比例,按受访者年龄分组 - 按时间从上次分娩以来划分妇女 - 体重与身高、体重与年龄和身高与年龄的散点图 - 按单一年龄划分的男性和女性人口图 - 人口金字塔 每个数据质量表的结果均在最终报告的附录中呈现,并在外部资源部分给出。 缺失数据的呈现规则是,如果缺失数据的案例百分比达到1%或更多,则呈现缺失数据的列。具有背景特征(例如教育)缺失数据的案例包括在表中,但缺失数据行被抑制,并在报告底部(而不是SPSS输出)注明。 数据清理 --------------------------- 在整个处理过程中进行了数据编辑,包括: a) 办公室编辑和编码 b) 数据录入期间 c) 结构检查和完整性 d) 次级编辑 e) SPSS数据文件的结构检查 有关数据编辑的详细文档可以在数据处理指南中找到。 响应率 --------------------------- 在选定的15,000户样本中,发现14,984户有人居住。其中14,564户被成功访谈,家庭响应率为97.2%。在受访的家庭中,确定了14,719名(15-49岁)妇女。其中,14,570名被成功访谈,响应率为99.0%。此外,家庭问卷中列出了4,424名5岁以下儿童。其中,完成了4,416份问卷,响应
提供机构:
nada-demo.ihsn.org
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作