SWZ_2010_MICS_v01_M
Multiple Indicator Cluster Survey 2010
Name | Country code |
---|---|
Kingdom of Eswatini | SWZ |
Multiple Indicator Cluster Survey - Round 4 [hh/mics-4]
The Multiple Indicator Cluster Survey, Round 4 (MICS4) is the forth round of MICS surveys, previously conducted around 1995 (MICS1), 2000 (MICS2), and 2005-2007 (MICS3). MICS was originally developed to support countries measure progress towards an internationally agreed set of goals that emerged from the 1990 World Summit for Children.
The fourth round of Multiple Indicator Cluster Surveys (MICS4) is scheduled for 2009-2011 and survey results are expected to be available from 2010 onwards. MICS4 data allow countries to better monitor progress toward national goals and global commitments, including the Millennium Development Goals (MDGs) as the target year 2015 approaches.
Information on more than 20 of the MDG indicators is being collected through MICS4, offering one of the largest single sources of data for MDG monitoring. MICS4 continues to address emerging issues and new areas of interest, with validated, standard methodologies in collecting relevant data. It also helps countries capture rapid changes in key indicators.
Sample survey data [ssd]
The scope of the Multiple Indicator Cluster Survey includes:
National
The survey covered all de jure household members (usual residents), all women aged between 15-49 years, all children under 5 living in the household, and all men aged 15-59 years.
Name |
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United Nations Children’s Fund |
Central Statistical Office |
Name | Role |
---|---|
Deputy Prime Minister’s Office | Survey implementation |
Ministry of Health | Survey implementation |
Ministry of Education and Training | Survey implementation |
Ministry of Natural Resources and Energy | Survey implementation |
National Emergency Response Council on HIV/AIDS (NERCHA) | Survey implementation |
United Nations agencies | Survey implementation |
Name | Role |
---|---|
Government of the Kingdom of Swaziland | Financial support |
United Nations Children’s Fund | Financial support |
United Nations Population fund | Financial support |
National Emergency Response Council on HIV/AIDS | Financial support |
Joint United Nations Programme on HIV/AIDS | Financial support |
The primary objective of the sample design for the 2010 Kingdom of Eswatini MICS was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the four regions of the country (Hhohho, Manzini, Shiselweni and Lubombo).
A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The 2006/07 Swaziland Demographic Health Survey (SDHS) collected many of the indicators in the MICS. Therefore, the results of the 2006/07 SDHS and the sample design were used as a reference in finalizing the sample design for the 2010 Swaziland MICS. In the survey, most of the indicators will be tabulated at the national level, urban and rural domains, and for the four regions as in the case of the 2006/07 SDHS.
The sampling frame for MICS comes from the recent Kingdom of Eswatini Census of Population and Housing data collected in 2007. The primary sampling units (PSUs) are the census enumeration areas (EAs). The EAs were created for the 2007 Census operations with well-defined boundaries identified on sketch maps. The number of households in an EA is based on the expected workload for one enumerator. According to the 2007 Census, the average number of households per EA is 103 (274 for rural EAs and 34 for urban EAs).
The sample size for a good household survey, such as the 2010 Kingdom of Eswatini MICS, is determined by the accuracy required for the estimates for each domain, as well as by the resource and operational constraints. The allocation of the sample EAs in each region to the rural and urban strata will be proportional to the number of households. Based on these criteria, the proposed allocation of sample EAs and households by region and rural and urban stratum results in a total sample of 365 EAs and 5,475 households.
The sampling procedures are more fully described in "Swaziland Multiple Indicator Cluster Survey 2010 - Final Report" pp.A1-A6.
Of the 5,475 households selected for the sample nationally, 5,074 households were found to be occupied. Of these, 4,834 households were interviewed successfully yielding a household response rate of 95 percent. Among the interviewed households, 4,956 women age 15–49 years and 4,646 men age 15–59 years were identified. Of this number, 4,688 women and 4,179 men were successfully interviewed, yielding a response rate of 95 percent and 90 percent respectively. In addition, 2,711 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 2,647, corresponding to a response rate of 98 percent. Overall response rates of 90, 86 and 93 percent are calculated for under-five’s, women’s and men’s interviews respectively.
Responses varied slightly by residence with higher rates for women and men in rural areas than in urban areas. The situation was the reverse for children under-five where rural areas had higher response rates than urban areas. The overall response rate for women, men and children under five years in rural areas were, however, higher than in urban areas. The main reason for non-response among households and eligible individuals was the failure to find these individuals at home despite several visits to the households. Regional differentials also exist with all the regions having a 90 percent or higher response rate for all the questionnaires with the exception of Hhohho and Shiselweni regions that had 88 and 89 percent response rate, respectively, for the men’s questionnaire.
The basic weight for each sample household is equal to the inverse of its probability of selection (calculated by multiplying the probabilities at each sampling stage). To make the estimates from the 2010 Swaziland MICS sample to be representative of the population, it is necessary to multiply the data by a sampling weight, or expansion factor.
As indicated in the previous section, the 365 EAs sampled for the 2010 Swaziland MICS were selected using the PPS methodology from the total 2,065 EAs in the Census 2007, separately for each stratum. At the second stage 15 sample households are selected with equal probability from the listing for each sampled EA.
Computation and implementation of sample weights for the 2010 Swaziland MICS were carried out at the stratum level. This has been done to have a smoothed weight at the stratum level catering for the non-response and variations in the number of households at that level, and also to avoid unusual inflation or deflation in the weights due to variations in small number of cases at the EA level.
The sample weights were calculated as the stratum (11 sample domains) base, so each cluster within the same domain will take the same weights (of course different for household, women, men and children level). The weight variable was added to each dataset. This was performed by using the statistical software SPSS with an add variables feature under the data/merge files, the data sets were sorted by domain variable and were taken as a key variable during the process.
Although the weights were calculated by 11 domains, including three company towns/estates of Hhohho, Manzini and Lubombo, they are already the part of three of four main regions. These three ‘company towns/estates’ domains will be regarded as a part of the Hhohho, Manzini and Lubombo regions.
The 2010 Kingdom of Eswatini MICS consists of four main questionnaires including a household questionnaire, women’s and men’s questionnaires and a questionnaire for children under age five. The survey includes information on key indicators on the following topics:
Household questionnaire: age, sex, urban vs. rural residency, household composition, education of household members, household assets, water and sanitation, use of iodized salt, use of insecticidetreated nets (ITNs), orphanhood and vulnerability of children, child labor and child discipline.
Questionnaire for children under five: birth registration, early childhood development, infant and young child feeding, care of illness (including diarrhoea and pneumonia), malaria, immunization and anthropometry.
Women’s questionnaire: child mortality, birth history, desire for last birth, maternal an newborn health, illness symptoms, contraception, unmet need, marriage/union, sexual behaviour, HIV/AIDS, sexually transmitted infections (STIs), and attitudes towards domestic violence.
Men’s questionnaire: marriage/union, attitudes towards contraception, sexual behaviour, HIV/AIDS, STIs, male circumcision and attitudes towards domestic violence.
Start | End |
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2010-08-12 | 2010-11-27 |
Name |
---|
Central Statistical Office |
There is one supovisor for each of the 6 survey teams in the field.
A total of 67 interviewers (including some of the trainees of the training of trainers), two office editors, data entry administrators and supervisors participated in the main fieldwork training, conducted from 19 July to 7 August 2010. Office editors and data entry administrators and supervisors participated in the main training to get a better understanding of the questionnaires and survey techniques. The training included lectures on interviewing techniques, background presentations on the various themes, presentation and discussion of the questionnaires, local language (siSwati) discussion of the questionnaires, class exercises and mock interviews among trainees to acquire skills in the asking of questions. All interviewers were further trained in testing and identification of oedema, salt testing and taking of anthropometric (height and weight) measurements of under-five children. Towards the end of the training period, trainees spent three days conducting field interviews in different urban and rural settings. Areas outside the sample were selected to provide the field staff a better understanding of working in different environments.
Supervisors and interviewers were selected based on their performance in the field practices, participation in class, assessment tests, fluency and understanding of siSwati and leadership qualities. A total of 48 out of the 67 enumerators trained were selected to be part of the data collection team. The remaining trainees were put on stand-by teams and were called upon as and when the need arose.
Data collection commenced on 12 August and ended on 27 November 2010. The data were collected by six teams. Each team was made up of six interviewers, a driver, a field editor, a measurer and a supervisor.
Data entry commenced on 3 September after an initial training and ended on 17 December 2010. Data were entered on 10 computers by 10 data entry operators and two data entry supervisors using the CSPro software. In order to ensure quality control, all questionnaires were double entered and two secondary editors complemented the efforts of entry supervisors to perform internal consistency checks. Procedures and standard programmes developed under the global MICS4 survey were adapted, based on the modified Swaziland MICS questionnaires, and used throughout the processing. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software programme, and syntax and tabulation plans developed for the global MICS4 were customized for this purpose.
The sample of respondents selected in the 2010 Kingdom of Eswatini MICS is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey results.
The following sampling error measures are presented in this appendix for each of the selected indicators:
Standard error (se): Sampling errors are usually measured in terms of standard errors for particular indicators (means, proportions etc). A standard error is the square root of the variance. The Taylor linearization method is used for the estimation of standard errors.
Coefficient of variation (se/r) is the ratio of the standard error to the value of the indicator.
Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling. The square root of the design effect, called the design factor (deft) is used to show the efficiency of the sample design. A deft value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a deft value above 1.0 indicates the increase in the standard error due to the use of a more complex sample design.
Confidence limits are calculated to show the interval within which the true value for the population can be reasonably assumed to fall. For any given statistic calculated from the survey, the value of that statistics will fall within a range of plus or minus two times the standard error (p + 2.se or p – 2.se) of the statistic in 95 percent of all possible samples of identical size and design. For the calculation of sampling errors from the MICS data, the SPSS Complex Samples module has been used. The results are shown in the tables that follow. In addition to the sampling error measures described above, the tables also include weighted and unweighted counts of denominators for each indicator.
Sampling errors are calculated for indicators of primary interest, for the national total, for the regions, and for urban and rural areas. Two of the selected indicators are based on households, eight are based on household members, 21 are based on women, 19 are based on children under five and 12 are based on men. All indicators presented here are in the form of proportions.
A series of data quality tables are available to review the quality of the data and include the following:
The results of each of these data quality tables are shown in appendix D in document "Swaziland Multiple Indicator Cluster Survey 2011 - Final Report" pp.A38-A55.
Name | Affiliation | URL | |
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Childinfo | UNICEF | http://www.childinfo.org/mics4_surveys.html | mics@unicef.org |
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
---|---|
yes | Users of the data agree to keep confidential all data contained in these datasets and to make no attempt to identify, trace or contact any individual whose data is included in these datasets. |
Use of the dataset must be acknowledged using a citation which would include:
Example:
United Nations Children's Fund, Central Statistical Office of the Kingdom of Eswatini. Kingdom of Eswatini Multiple Indicator Cluster Survey (MICS) 2010, Ref. SWZ_2010_MICS_v01_M. Dataset downloaded from [url] on [date].
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Name | Affiliation | URL | |
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A. M. Zwanec | Central Statistics Office | director@swazistats.org.sz | |
J. Gulaid | UNICEF | jgulaid@unicef.org | |
The World Bank Microdata Library | The World Bank | microdata@worldbank.org | http://microdata.worldbank.org |
DDI_SWZ_2010_MICS_v01_M
Name | Affiliation | Role |
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Development Data Group | The World Bank | Documentation of the DDI |
2013-01-14
Version 01 (January 2013)
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