UNICEF assists countries in collecting and analyzing data in order to fill data gaps for monitoring the situation of children and women through its international household survey initiative the Multiple Indicator Cluster Surveys (MICS).
MICS 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 where experts from developing countries are trained on various aspects of MICS (questionnaire content, sampling and survey implementation, data processing, data quality and data analysis, and report writing and dissemination).
Since the mid-1990s, the MICS has enabled many countries to produce statistically sound and internationally comparable estimates of a range of indicators in the areas of health, education, child protection and HIV/AIDS. MICS findings have been used extensively as a basis for policy decisions and programme interventions, and for the purpose of influencing public opinion on the situation of children and women around the world.
MICS1 (1995) - The MICS was originally developed in response to the World Summit for Children to measure progress towards an internationally agreed set of mid-decade goals. The first round of MICS was conducted around 1995 in more than 60 countries.
MICS2 (2000) - 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.
MICS3 (2005-2006) - The third round of MICS, which was carried out in over 50 countries in 2005-06, has been an important data source for monitoring the Millennium Development Goals with 21 MDG indicators collected through MICS3 (particularly indicators related to health, education and mortality). MICS3 was also a monitoring tool for other international goals including the World Fit for Children, the UNGASS targets on HIV/AIDS and the Abuja targets for malaria.
MICS4 (2009-2011) - In response to an increased demand for data all over the world, starting from MICS4, UNICEF will be prepared to provide assistance to countries at more frequent intervals - every three years instead of every five years. This will provide the opportunity for countries to capture rapid changes in key indicators, particularly the MDGs.
The 2006 Guyana Multiple Indicator Cluster Survey has as its primary objectives:
• To provide up-to-date information for assessing the situation of children and women in Guyana;
• To furnish data needed for monitoring progress toward goals established in the Millennium Development Goals, 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 Guyana and to strengthen technical expertise in the design, implementation, and analysis of such systems.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Children under 5 years
The scope of Guyana 2006 MICS includes:
- Household (extended) listing form (demographic information)
- Water and sanitation
- Household characteristics
- Children orphaned & made vulnerable by HIV/AIDS
- Child labor
- Child Discipline
QUESTIONNAIRE FOR INDIVIDUAL WOMEN
- Child mortality
- Maternal and newborn health
- Contraception and unmet need
- Attitudes toward domestic violence
QUESTIONNAIRE FOR CHILDREN UNDER FIVE
- Birth registration and early learning
- Child development
- Care of illness
Producers and sponsors
Bureau of Statistics
United Nations Children's Fund
The sample for the Guyana Multiple Indicator Cluster Survey (MICS3) 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, and interior and coastal areas. In considering the urban/rural distinction, it should be borne in mind that all the urban areas of the country are located within the coastal region and the entire interior region is considered to be rural.
Coastal and interior areas were identified as the main sampling domains and the sample was selected in two stages. Within the coastal and interior areas, 160 and 60 census enumeration district areas respectively were selected with probability proportional to size. After a household listing was carried out within the selected enumeration areas, a circular systematic sample of twenty- four (24) households was drawn. All of the selected enumeration areas were visited during the fieldwork period. The sample was stratified by urban and rural area and is not self-weighting. For reporting national level results, sample weights are used.
A more detailed description of the sample design can be found in Appendix A of the report.
Dates of Data Collection
Data Collection Mode
Three sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect information on all de jure household members, the household, and the dwelling; 2) a women’s questionnaire administered in each household to all women aged 15-49 years; and 3) an under-5 questionnaire, administered to mothers or caretakers of all children under 5 living in the household. The questionnaires included the following modules:
The Household Questionnaire included the following modules:
• Household (Extended) Listing
• Water and Sanitation
• Household Characteristics
• Insecticide Treated Nets (administered only in the high-risk malaria areas i.e. interior of Guyana)
• Child Labour
• Child Discipline
The Questionnaire for Individual Women was administered to all women aged 15-49 years living in the households, and included the following modules:
• Child Mortality
• Diphtheria Tetanus (administered to women who had at least one live birth within the 2 years prior to interview)
• Maternal and Newborn Health (administered to women who had at least one live birth within the 2 years prior to interview)
• Marriage/Union Status
• Contraception and Unmet Needs
• Attitudes Towards Domestic Violence
• HIV/AIDS Knowledge and Awareness
The Questionnaire for Children Under Five was administered to mothers or caretakers of children under 5 years of age living in the households. Normally, the questionnaire was administered to mothers of under-5 children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed. The questionnaire included the following modules:
• Birth Registration and Early Learning
• Child Development
• Care of Illness
• Malaria (administered only in the high-risk malaria areas i.e. interior of Guyana)
The Guyana MICS3 questionnaires are based on the English version of the MICS3 model questionnaire. These model questionnaires were adapted and modified, with consultation with the Guyana MICS3 Technical Steering Committee, to reflect national situations. The modified version of the questionnaires was pre-tested in six clusters in both urban and rural areas during February, 2006. However, malaria related modules were not tested since the pre-test focused on the coast of Guyana where malaria is largely considered non-existent. Based on the results of the pre-test further modifications were made to the wording and the response categories of the questionnaires.
Data were entered using the CSPro software. The data were entered on three microcomputers and carried out by three data entry operators and one data entry supervisor. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS3 project and adapted to the Guyana questionnaire were used throughout. Data processing began in June, 2006, some three months after the start data collection and was completed in January, 2007.
Estimates of Sampling Error
The sample of respondents selected in the Guyana Multiple Indicator Cluster Survey 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). 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 (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 MICS data, SPSS Version 14 Complex Samples module has been used. The results are shown in the tables in Appendix C of the report. In addition to the sampling error measures described above, the tables also include weighted and unweighted counts of denominators for each indicator.
MICS Programme Manager
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