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.
The 2010 Sierra Leone Multiple Indicator Cluster Survey (MICS4) is a nationally representative survey of households, women, and children. The main objectives of the survey are (i) to provide current information for assessing the present situation of women and children in Sierra Leone-including the identification of vulnerable groups and of disparities among groups-in order to inform policies and interventions; (ii) to produce data to monitor progress toward the achievement of targets and goals that include the Millennium Development Goals (MDGs) and World Fit For Children; and, (iii) to contribute to the improvement of national statistical, data and monitoring systems in Sierra Leone and to strengthen national capacity and technical expertise in the design and implementation of such systems. Interviews were successfully completed in 11,394 households drawn from all districts of Sierra Leone.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- v01: Edited, anonymous datasets for public distribution.
The scope of the Multiple Indicator Cluster Survey includes:
- Household: household listing form, education, water and sanitation, household characteristics, insecticide-treated nets, indoor residual spraying, child labour, child discipline, handwashing and salt iodisation.
- Women: woman's background, child mortality, tetanus toxoid, desire for last birth, maternal and newborn health, illness symptoms, contraception, unmet need, female genital mutilation/cutting, attitudes towards domestic violence, marriage/union, sexual behavior and HIV/AIDS.
- Children: child's age, birth registration, early childhood development, breastfeeding, care of illness, malaria, immunization and anthropometry.
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.
Producers and sponsors
United Nations Children’s Fund
Statistics Sierra Leone
United Nations Children’s Fund
Financial and technical support
Ministry of Finance and Economic Development
Ministry of Education, Science and Technology
Ministry of Energy and Water Resources (Water Division)
Ministry of Health and Sanitation
Ministry of Information and Communications
Ministry of Local Government and Rural Development
Ministry of Social Welfare, Gender and Children’s Affairs
United Nations Population Fund
United Nations World Food Programme
World Health Organization
The primary objective of the sample design for the Sierra Leone Multiple Indicator Cluster Survey was to produce statistically reliable estimates of most indicators at the national level, for urban and rural areas, for the four regions of the country (Northern Province, Eastern Province, Southern Province, and the West), and finally, for the fourteen districts of Sierra Leone. Urban and rural areas in each of the fourteen districts were defined as the sampling strata.
A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.
The target sample size for the Sierra Leone MICS was calculated as 12,000 households. For the calculation of the sample size, the key indicator used was the proportion of children aged 12-23 months who are vaccinated with DPT3 by one year of age.
The resulting number of households to be selected that was calculated using the formula above was 11,990, which was rounded up to 12,000 households. It was decided that the cluster size would be 25 households, based on a number of considerations that include the available budget and the estimated time that was required for a team to completely survey one cluster. Dividing the total number of households by the number of households per cluster, it was calculated that a total of 480 clusters was required.
The MICS4 Steering Committee made a decision to sample a minimum of 30 enumeration areas (EAs) in each district in order to generate district-level estimates with a maximum precision level of ± 12 percent. Using a probability proportion to size (pps) method to allocate clusters to districts would have resulted in several districts with less than 30 EAs. The decision was thus taken to create a weighted sample (i.e., not pps) that contained at least 30 clusters per district. Other districts were under-sampled to compensate for over-sampling the smaller districts. The number of EAs for each district that was included in the sample is listed in the table below. In each district, the EAs (primary sampling units) were distributed to urban and rural domains, proportional to the size of urban and rural populations in that district.
The sampling procedures are more fully described in "Sierra Leone Multiple Indicator Cluster Survey 2010 - Final Report" pp.130-135.
Of the 11,923 households selected for the sample, 11,578 were found to be occupied. Of these, 11,394 were successfully interviewed for a household response rate of 98.4 percent. In the interviewed households, 14,068 women (age 15-49 years) were identified. Of these, 13,359 were successfully interviewed, yielding a response rate of 95.0 percent within interviewed households. In addition, 8,799 children under age five were listed in the household questionnaire. Questionnaires were completed for 8,600 of these children, which corresponds to a response rate of 97.7 percent within interviewed households. Overall response rates of 93.5 and 96.2 percent are calculated for the women's and under-5's interviews respectively.
Ninety-seven percent of sampled households were found to be occupied. The household response rate was slightly lower in the West as compared to other provinces, primarily due to difficulties finding household members at home in Freetown. Response rates for women and children were very similar across provinces and areas of residence. Overall response rates were at an acceptable level.
Sample weights were calculated and these were used in the subsequent analyses of the survey data.
Since the estimated number of households in each enumeration area (PSU) in the sampling frame used for the first stage selection and the updated number of households in the enumeration area from the listing were different, individual sampling fractions for households in each sample enumeration area (cluster) were calculated. The sampling fractions for households in each cluster therefore included the first stage probability of selection of the enumeration area in that particular sampling stratum and the second stage probability of selection of a household in the sample enumeration area cluster.
A second component in the calculation of sample weights takes into account the level of non-response for the household and individual interviews. The adjustment for household non-response is equal to the inverse value of: RRh = Number of interviewed households in stratum h/ Number of occupied households listed in stratum h
The non-response adjustment factors for women's and under-5's questionnaires are applied to the adjusted household weights. Numbers of eligible women and under-5 children were obtained from the roster of household members in the Household Questionnaire for households where interviews were completed.
The design weights for the households were calculated by multiplying the above factors for each enumeration area. These weights were then standardized (or normalized), one purpose of which is to make the weighted sum of the interviewed sample units equal the total sample size at the national level. Normalization is performed by dividing the aforementioned design weights by the average design weight at the national level. The average design weight is calculated as the sum of the design weights divided by the unweighted total. A similar standardization procedure was followed in obtaining standardized weights for the women's and under-5's questionnaires. Adjusted (normalized) weights for households varied between 0.0494 and 4.4452 in the 480 sample enumeration areas (clusters).
Dates of Data Collection
Data Collection Mode
There is one supervisor for each of the 24 survey teams in the field.
Data Collection Notes
Supervisors and enumerators participated in separate trainings prior to the MICS4 fieldwork. The three-day training of supervisors was conducted in September 2010. All supervisors then participated as trainers in the nine-day training of enumerators. Training included lectures on interviewing techniques and the contents of the questionnaires, interviews of respondents by groups of trainees to gain practice in asking questions, and then community-level interviews with actual respondents. Towards the end of the training period, trainees spent a full day conducting practice interviews in the rural West outside of Freetown.
Actual survey data were collected by 24 teams; each team was comprised of four enumerators, one driver and a supervisor. Fieldwork began in early October 2010 and concluded in December 2010.
Statistics Sierra Leone
The questionnaires for the Generic MICS were structured questionnaires based on the MICS4 model questionnaire with some modifications and additions. Household questionnaires were administered to a knowledgeable adult living in the household. The household questionnaire includes household listing form, education, water and sanitation, household characteristics, insecticide-treated nets, indoor residual spraying, child labour, child discipline, handwashing and salt iodisation.
In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. The questionnaire for children under 5 years of age was administered to mothers or caregivers of all children under 5 years of age living in the households.
The women's questionnaire includes woman's background, child mortality, tetanus toxoid, desire for last birth, maternal and newborn health, illness symptoms, contraception, unmet need, female genital mutilation/cutting, attitudes towards domestic violence, marriage/union, sexual behavior and HIV/AIDS.
The children's questionnaire includes child's age, birth registration, early childhood development, breastfeeding, care of illness, malaria, immunization and anthropometry.
Data were entered using CSPro software. Data processing was carried out by 30 data entry operators and 2 data entry supervisors. 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 MICS programme and adapted to the Sierra Leone questionnaire were used throughout. Data processing began simultaneously with data collection in October 2010 and was completed in June 2011. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program (Version 18). The analysis was carried out using the model syntax and tabulation plans developed by UNICEF.
Estimates of Sampling Error
Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data.
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 of the estimate. 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, and is a measure of the relative sampling error.
- 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 in relation to the precision. 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, with a specified level of confidence. For any given statistic calculated from the survey, the value of that statistic will fall within a range of plus or minus two times the standard error (r + 2.se or r - 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, the SPSS Version 18 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 at the national, regional and location (i.e., urban/rural) levels. Two of the selected indicators are based on households, eight are based on household members, 23 are based on women, and 20 are based on children under 5. 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:
- Age distribution of the household population
- Age distribution of eligible and interviewed women
- Age distribution of under-5s in household and children under 5 questionnaires
- Women's completion rates by socio-economic characteristics of households
- Completion rates for under-5 questionnaires by socio-economic characteristics of households
- Completeness of reporting
- Completeness of information for anthropometric indicators
- Heaping in anthropometric measurements
- Observation of bed nets and places for hand washing
- Observation of women's health cards
- Observation of children under 5 birth certificates
- Observation of vaccination cards
- Presence of mother in the household and the person interviewed for the under-5 questionnaire
- Selection of children age 2-14 years for the child discipline module
- School attendance by single age
The results of each of these data quality tables are shown in appendix D in document "Sierra Leone Multiple Indicator Cluster Survey 2010 - Final Report" pp.149-157.
Mohamed King Koroma
Statistics Sierra Leone
The World Bank Microdata Library
The World Bank
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:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
United Nations Children's Fund, Statistics Sierra Leone. Sierra Leone Multiple Indicator Cluster Survey (MICS) 2010, Ref. SLE_2010_MICS_v01_M. Dataset downloaded from [url] on [date].
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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.