Multiple Indicator Cluster Survey 2006 - Syrian Arab Republic

Abstract
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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 such as the Millennium Development Goals (MDGs) indicators. It is a flexible tool that is reasonably inexpensive and relatively quick to implement.

Background
MICS was originally developed in response to the 1990 World Summit for Children to measure progress towards an internationally agreed set of goals. The first round of MICS was conducted around 1995 in more than 60 countries. A second round of surveys was conducted in 2000 (around 65 surveys), and resulted in an increasing wealth of data to monitor the situation of children and women. For the first time it was possible to monitor trends in many indicators and set baselines for other indicators.

Purpose
Information on around 20 of the 48 MDG indicators will be collected in the current round of MICS, offering the largest single source of data for MDG monitoring. The current round of MICS is thus 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.

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).

HOUSEHOLD: Household Listing, Education, Water and Sanitation, Household Characteristics, and Child Labour.

WOMEN: Child Mortality, Tetanus Toxoid, Maternal and Newborn Health, Marriage, Contraception, and HIV/AIDS.

CHILDREN: Birth Registration and Early Learning, Vitamin A, Breastfeeding, Care of Illness, Immunization, and Anthropometry.

The surveys are typically carried out by government organizations, 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
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The survey is nationally representative and covers the whole of Syria.

Analysis unit
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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
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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
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Sample survey data [ssd]

Sampling procedure
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The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2006 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

The sample for the Multiple Indicator Cluster Survey of the Syrian Arab Republic was designed to estimate a number of indicators on the situation of women and children at the national, and governorate levels, for urban and rural areas. The framework of the 2004 Overall Census of Inhabitants and Dwellings was used as the sampling frame. The sample was selected in two stages in each area. In the first stage, the clusters were drawn as census areas in proportion to size with a total of (1000) clusters. In the second stage, the counting units were drawn (households) in a regular arbitrary manner. The sample is not selfweighting. For reporting national level results, sample weights are used.

Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.

No replacement of households was permitted in case of non-response or non-contactable households. Adjustments were made to the sampling weights to correct for non-response, according to MICS standard procedures.

The sampling procedures are more fully described in the sampling appendix of the final report and can also be found in the list of technical documents within this archive.

Sampling deviation
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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
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Face-to-face [f2f]

Research instrument
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The questionnaires for the Syria 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 and relationship with the household head. The household questionnaire includes household listing, education, water and sanitation, household characteristics, and child labour

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, tetanus toxoid, maternal and newborn health, marriage, contraception, and HIV/AIDS.

The children's questionnaire includes children's characteristics, birth registration and early learning, vitamin A, breastfeeding, care of illness, immunization, and anthropometry.

The questionnaires are based on the MICS3 model questionnaire and were pre-tested during February, 2006. Based on the results of the pre-test, modifications were made to the wording of the questionnaires.

In addition to the administration of questionnaires, fieldwork teams measured the weights and heights of children age under-five years.

Cleaning operations
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Data were processed in clusters, with each cluster being processed as a complete unit through each stage of data processing. Each cluster goes through the following steps:
1) Questionnaire reception
2) Office editing and coding
3) Data entry
4) Structure and completeness checking
5) Verification entry
6) Comparison of verification data
7) Back up of raw data
8) Secondary editing
9) Edited data back up
After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:
10) Export to SPSS in 4 files (hh - household, hl - household members, wm - women, ch - children under 5)
11) Recoding of variables needed for analysis
12) Adding of sample weights
13) Calculation of wealth quintiles and merging into data
14) Structural checking of SPSS files
15) Data quality tabulations
16) Production of analysis tabulations

Details of each of these steps can be found in the data processing documentation, data editing guidelines, data processing programs in CSPro and SPSS, and tabulation guidelines.

Data entry was conducted by 30 data entry operators in one shifts, supervised by 2 data entry supervisors, using a total of 31 computers (15 data entry computers plus one supervisors computer). All data entry was conducted at the CBS SYRIA head office using manual data entry. For data entry, CSPro version 2.6.007 was used with a highly structured data entry program, using system controlled approach, that controlled entry of each variable. All range checks and skips were controlled by the program and operators could not override these. A limited set of consistency checks were also included inthe data entry program. In addition, the calculation of anthropometric Z-scores was also included in the data entry programs for use during analysis. Open-ended responses ("Other" answers) were not entered or coded, except in rare circumstances where the response matched an existing code in the questionnaire.

Structure and completeness checking ensured that all questionnaires for the cluster had been entered, were structurally sound, and that women's and children's questionnaires existed for each eligible woman and child.

100% verification of all variables was performed using independent verification, i.e. double entry of data, with separate comparison of data followed by modification of one or both datasets to correct keying errors by original operators who first keyed the files.

After completion of all processing in CSPro, all individual cluster files were backed up before concatenating data together using the CSPro file concatenate utility.

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 in the MICS Manual (http://www.childinfo.org/mics3_manual.html)

Response rate
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Out of (20022) households selected for sampling, (19870) were actually found, while the dwellings of the remaining households were either not occupied, or else the households themselves were out. (19019) households were successfully interviewed yielding a household response rate of (95.7) percent. In the interviewed households (25563) women aged 15-49 were identified. Out of these (25026) women were interviewed, yielding a response rate of (97.9) percent. The number of children under five listed in the household questionnaire totaled (11104). Out of these, (11017) children were interviewed, which corresponds to a response rate of 99.2%. The overall response rate for the women’s questionnaires was (93.7) percent, while the one for the children under five was (95) percent. The response rate was similar in urban and rural areas, as Table (HH1) shows.

Sampling error estimates
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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).

Data appraisal
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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.

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
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联合国儿童基金会（UNICEF）开发的多个指标集群调查（MICS）是一项旨在帮助各国填补监测人类发展总体状况以及儿童和妇女特定状况数据空白的家庭调查项目。

MICS能够产生统计上可靠、国际上可比较的社会指标估计，例如千年发展目标（MDGs）指标。它是一种灵活的工具，成本相对较低，实施速度较快。

背景
MICS最初是为了响应1990年世界儿童峰会而开发的，旨在衡量朝着国际上达成一致的目标的进展。第一次MICS于1995年在大约60个国家进行。2000年进行了第二轮调查（约65次调查），为监测儿童和妇女的状况积累了越来越多的数据。首次有可能监测许多指标的趋势，并为其他指标设定基线。

目的
在当前一轮的MICS中，将收集大约48个MDG指标中的20个指标的信息，为MDG监测提供最大单一数据来源。因此，当前一轮的MICS旨在为千年发展目标（MDGs）、世界儿童适宜环境（WFFC）以及其他主要国际承诺（如联合国大会特别会议（UNGASS）关于艾滋病和 Abuja 关于疟疾的目标）提供监测工具。

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岁妇女问卷和5岁以下儿童问卷（由母亲或监护人填写）。

家庭：家庭登记、教育、水和卫生、家庭特征和儿童劳动。

妇女：儿童死亡率、破伤风类毒素、孕产妇和新生儿健康、婚姻、避孕和艾滋病。

儿童：出生登记和早期学习、维生素A、母乳喂养、疾病护理、免疫和人体测量学。

调查通常由政府机构执行，在联合国儿童基金会和其他合作伙伴的支持和协助下进行。通过一系列区域性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；报告编写和传播。

地理覆盖范围
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调查在全国范围内进行，覆盖整个叙利亚。

分析单位
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家庭（定义为通常一起生活和进食的人员群体）

法定家庭成员（定义为通常居住在家庭中的人员，可能包括前一天晚上未在家庭中过夜但通常居住在家庭中的人，但不包括前一天晚上在家庭中过夜但通常不住在家庭中的访客）

15-49岁的妇女

0-4岁的儿童

总体
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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
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样本调查数据 [ssd]

抽样程序
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抽样设计的主要目标是提供关于世界儿童适宜环境宣言四大领域的当前和可靠的估计，包括促进健康生活；提供优质教育；防止虐待、剥削和暴力；以及抗击艾滋病。2006年MICS的人口覆盖范围定义为所有15-49岁的妇女和所有5岁以下的儿童。选择了一个家庭样本，并采访了这些家庭的所有15-49岁的常住居民妇女。此外，还采访了所有5岁以下常住居民的母亲的护理者，了解儿童。

叙利亚阿拉伯共和国的多个指标集群调查样本旨在估计国家层面和省层面、城市和农村地区妇女和儿童状况的一系列指标。使用2004年人口和住宅总普查框架作为抽样框架。在每个地区，样本选择分为两个阶段。在第一阶段，按规模比例抽取集群作为普查区域，总共有（1000）个集群。在第二阶段，以常规任意方式抽取计数单位（家庭）。样本不具有自加权性。在报告国家层面结果时，使用样本权重。

根据标准MICS数据收集规则，如果访问时实际上有多个家庭，则：a）如果选定的家庭包含两个家庭，则两个家庭都被采访；或者b）如果选定的家庭包含3个或更多家庭，则只采访被命名为首脑的家庭。

在非响应或无法联系的家庭的情况下，不允许替换家庭。根据MICS标准程序对抽样权重进行调整以纠正非响应。

抽样程序在最终报告的抽样附录中进行了更全面的描述，也可以在本存档中的技术文件列表中找到。

抽样偏差
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没有对原始样本设计做出重大偏差。所有样本枚举区域都已访问并成功采访，响应率良好。

数据收集方式
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面对面 [f2f]

研究工具
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叙利亚MICS的问卷是基于MICS3模型问卷进行修改和补充的结构化问卷。在每户家庭中进行了家庭问卷，收集了关于家庭成员的各种信息，包括性别、年龄和与家庭首脑的关系。家庭问卷包括家庭登记、教育、水和卫生、家庭特征和儿童劳动。

除了家庭问卷外，还向每户家庭的15-49岁妇女和5岁以下儿童进行了问卷。对于儿童，问卷由母亲或儿童的护理者填写。

妇女问卷包括妇女特征、儿童死亡率、破伤风类毒素、孕产妇和新生儿健康、婚姻、避孕和艾滋病。

儿童问卷包括儿童特征、出生登记和早期学习、维生素A、母乳喂养、疾病护理、免疫和人体测量学。

问卷基于MICS3模型问卷，并于2006年2月进行预测试。根据预测试的结果，对问卷的措辞进行了修改。

除了问卷的发放外，现场工作小组还测量了5岁以下儿童的体重和身高。

数据处理操作
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数据以集群为单位进行处理，每个集群作为数据处理每个阶段的完整单元进行处理。每个集群经过以下步骤：
1）问卷接收
2）办公室编辑和编码
3）数据录入
4）结构和完整性检查
5）验证录入
6）验证数据的比较
7）原始数据的备份
8）二级编辑
9）编辑数据的备份
在处理所有集群后，将所有数据连接在一起，然后对所有数据文件完成以下步骤：
10）导出为SPSS 4个文件（hh - 家庭，hl - 家庭成员，wm - 女性，ch - 5岁以下儿童）
11）对分析所需的变量进行重新编码
12）添加样本权重
13）计算财富五分位数并将其合并到数据中
14）SPSS文件的结构检查
15）数据质量表格
16）分析表格的生产

每个步骤的详细信息可以在数据处理文档、MICS手册中的数据编辑指南、CSPro和SPSS中的数据处理程序以及表格指南中找到。

数据录入由30名数据录入操作员在一个班次内进行，由2名数据录入监督员监督，共使用31台计算机（15台数据录入计算机和1台监督员计算机）。所有数据录入都在叙利亚国家统计局总部使用手动数据录入进行。对于数据录入，使用了CSPro版本2.6.007，具有高度结构化的数据录入程序，采用系统控制方法，控制每个变量的录入。所有范围检查和跳过都由程序控制，操作员无法覆盖这些。数据录入程序还包括有限的一致性检查。此外，还将在分析中使用的人体测量学Z分数的计算包括在数据录入程序中。开放式回答（“其他”回答）除非在罕见情况下回答与问卷中现有的代码匹配，否则不进行或不编码。

结构和完整性检查确保所有集群的问卷都已录入，结构良好，并为每个符合条件的妇女和儿童存在妇女和儿童的问卷。

使用独立验证对所有变量进行了100%的验证，即数据的双录入，随后单独比较数据，然后修改一个或两个数据集以纠正原始操作员首次键入文件时的键入错误。

在CSPro中完成所有处理之后，在将数据连接在一起之前，对所有单个集群文件进行了备份。

数据编辑在处理过程中的多个阶段进行（见其他处理），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）二级编辑
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MICS手册中的数据处理指南中找到。

响应率
---------------------------
在（20022）个选定的抽样家庭中，实际上找到了（19870）个，而其余家庭的住宅要么无人居住，要么家庭本身不存在。（19019）个家庭成功接受了采访，家庭响应率为（95.7）%。在采访的家庭中，确定了（25563）名15-49岁的妇女。在这些妇女中，（25026）名妇女接受了采访，响应率为（97.9）%。家庭问卷中列出的5岁以下儿童总数为（11104）。在这些儿童中，（11017）名儿童接受了采访，响应率为99.2%。妇女问卷的整体响应率为（93.7）%，而5岁以下儿童的响应率为（95）%。如表（HH1）所示，城市和农村地区的响应率相似。

抽样误差估计
---------------------------
样本调查的估计受到两种类型误差的影响：1）非抽样误差和2）抽样误差。非抽样误差是数据收集和数据处理实施过程中出现的错误的结果。在实施2006年MICS期间，做出了大量努力来最大限度地减少此类错误，但是非抽样误差是不可避免的，并且难以进行统计分析。

抽样误差可以统计地进行评估。2006年MICS的受访者样本只是从同一人口中可能选择的许多样本之一，使用相同的设计和预期大小。这些样本中的每一个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变异性的指标，尽管变异程度并不完全清楚，但可以从调查结果中估计出来。抽样误差以特定统计量（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，其中可以假设真实值落在人口中。

如果受访者样本是简单随机样本，则可以使用简单的公式来计算抽样误差。但是，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。已使用SPSS复杂样本模块计算了2006年MICS的抽样误差。此模块使用Taylor线性化方法估计调查估计的方差，这些估计是均值或比例。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。

已为所选的一组统计量（所有这些都是由于Taylor线性化方法的限制而成为比例）计算了国家样本、城市和农村地区以及五个地区之一的抽样误差。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使用简单随机样本计算的标准误差之比），以及95%置信区间（±2个标准误差）。

数据评估
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一系列数据质量表格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
符合条件的妇女和接受采访的妇女年龄分布
符合条件的儿童和接受母亲或护理者采访的儿童的年龄分布
5岁以下儿童按3个月组别的年龄分布
边界上的年龄和时期比率
选定变量上缺失信息的观测值百分比
家庭中是否有母亲和为5岁以下儿童问卷采访的人
按单一年龄的学校出席率
出生儿童中存活和死亡儿童的性别比，按受访者年龄分组
按分娩时间划分的妇女分布
体重与身高、体重与年龄和身高与年龄的散点图
按单一年龄的男性和女性人口图
人口金字塔

每个这些数据质量表格的结果都在最终报告的附录中显示。

最终报告中表格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%或更高，则应呈现缺失数据的列。背景特征（例如教育）上的缺失数据案例包含在表格中，但缺失数据行被压制并在报告底部（而不是在SPSS输出中）注明。

响应率
---------------------------
在（20022）个选定的抽样家庭中，实际上找到了（19870）个，而其余家庭的住宅要么无人居住，要么家庭本身不存在。（19019）个家庭成功接受了采访，家庭响应率为（95.7）%。在采访的家庭中，确定了（25563）名15-49岁的妇女。在这些妇女中，（25026）名妇女接受了采访，响应率为（97.9）%。家庭问卷中列出的5岁以下儿童总数为（11104）。在这些儿童中，（11017）名儿童接受了采访，响应率为99.2%。妇女问卷的整体响应率为（93.7）%，而5岁以下儿童的响应率为（95）%。如表（HH1）所示，城市和农村地区的响应率相似。

抽样误差估计
---------------------------
样本调查的估计受到两种类型误差的影响：1）非抽样误差和2）抽样误差。非抽样误差是数据收集和数据处理实施过程中出现的错误的结果。在实施2006年MICS期间，做出了大量努力来最大限度地减少此类错误，但是非抽样误差是不可避免的，并且难以进行统计分析。

抽样误差可以统计地进行评估。2006年MICS的受访者样本只是从同一人口中可能选择的许多样本之一，使用相同的设计和预期大小。这些样本中的每一个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变异性的指标，尽管变异程度并不完全清楚，但可以从调查结果中估计出来。抽样误差以特定统计量（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，其中可以假设真实值落在人口中。

如果受访者样本是简单随机样本，则可以使用简单的公式来计算抽样误差。但是，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。已使用SPSS复杂样本模块计算了2006年MICS的抽样误差。此模块使用Taylor线性化方法估计调查估计的方差，这些估计是均值或比例。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。

已为所选的一组统计量（所有这些都是由于Taylor线性化方法的限制而成为比例）计算了国家样本、城市和农村地区以及五个地区之一的抽样误差。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使用简单随机样本计算的标准误差之比），以及95%置信区间（±2个标准误差）。

数据评估
---------------------------
一系列数据质量表格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
符合条件的妇女和接受采访的妇女年龄分布
符合条件的儿童和接受母亲或护理者采访的儿童的年龄分布
5岁以下儿童按3个月组别的年龄分布
边界上的年龄和时期比率
选定变量上缺失信息的观测值百分比
家庭中是否有母亲和为5岁以下儿童问卷采访的人
按单一年龄的学校出席率
出生儿童中存活和死亡儿童的性别比，按受访者年龄分组
按分娩时间划分的妇女分布
体重与身高、体重与年龄和身高与年龄的散点图
按单一年龄的男性和女性人口图
人口金字塔

每个这些数据质量表格的结果都在最终报告的附录中显示。

最终报告中表格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%或更高，则应呈现缺失数据的列。背景特征（例如教育）上的缺失数据案例包含在表格中，但缺失数据行被压制并在报告底部（而不是在SPSS输出中）注明。

响应率
---------------------------
在（20022）个选定的抽样家庭中，实际上找到了（19870）个，而其余家庭的住宅要么无人居住，要么家庭本身不存在。（19019）个家庭成功接受了采访，家庭响应率为（95.7）%。在采访的家庭中，确定了（25563）名15-49岁的妇女。在这些妇女中，（25026）名妇女接受了采访，响应率为（97.9）%。家庭问卷中列出的5岁以下儿童总数为（11104）。在这些儿童中，（11017）名儿童接受了采访，响应率为99.2%。妇女问卷的整体响应率为（93.7）%，而5岁以下儿童的响应率为（95）%。如表（HH1）所示，城市和农村地区的响应率相似。

抽样误差估计
---------------------------
样本调查的估计受到两种类型误差的影响：1）非抽样误差和2）抽样误差。非抽样误差是数据收集和数据处理实施过程中出现的错误的结果。在实施2006年MICS期间，做出了大量努力来最大限度地减少此类错误，但是非抽样误差是不可避免的，并且难以进行统计分析。

抽样误差可以统计地进行评估。2006年MICS的受访者样本只是从同一人口中可能选择的许多样本之一，使用相同的设计和预期大小。这些样本中的每一个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变异性的指标，尽管变异程度并不完全清楚，但可以从调查结果中估计出来。抽样误差以特定统计量（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，其中可以假设真实值落在人口中。

如果受访者样本是简单随机样本，则可以使用简单的公式来计算抽样误差。但是，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。已使用SPSS复杂样本模块计算了2006年MICS的抽样误差。此模块使用Taylor线性化方法估计调查估计的方差，这些估计是均值或比例。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。

已为所选的一组统计量（所有这些都是由于Taylor线性化方法的限制而成为比例）计算了国家样本、城市和农村地区以及五个地区之一的抽样误差。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使用简单随机样本计算的标准误差之比），以及95%置信区间（±2个标准误差）。

数据评估
---------------------------
一系列数据质量表格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
符合条件的妇女和接受采访的妇女年龄分布
符合条件的儿童和接受母亲或护理者采访的儿童的年龄分布
5岁以下儿童按3个月组别的年龄分布
边界上的年龄和时期比率
选定变量上缺失信息的观测值百分比
家庭中是否有母亲和为5岁以下儿童问卷采访的人
按单一年龄的学校出席率
出生儿童中存活和死亡儿童的性别比，按受访者年龄分组
按分娩时间划分的妇女分布
体重与身高、体重与年龄和身高与年龄的散点图
按单一年龄的男性和女性人口图
人口金字塔

每个这些数据质量表格的结果都在最终报告的附录中显示。

最终报告中表格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%或更高，则应呈现缺失数据的列。背景特征（例如教育）上的缺失数据案例包含在表格中，但缺失数据行被压制并在报告底部（而不是在SPSS输出中）注明。