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 Selected Districts of West Papua Province Multiple Indicator Cluster Survey (MICS) was conducted in 2011 by the Statistics Indonesia - Badan Pusat Statistik (BPS) - with technical and financial support from UNICEF. The survey provides valuable information on the situation of children and women in three selected districts of West Papua Province: Kaimana, Manokwari and Sorong, and was based, in large part, on the need to furnish up-to-date information on the situation of children and women in the selected districts of West Papua province to inform planning.
This survey forms part of the fourth round of the global MICS surveys initiated in 1995 to monitor the progress towards goals and targets emanating from recent international agreements: the Millennium Declaration, adopted by all 191 United Nations Member States in September 2000, and the Plan of Action of A World Fit For Children, adopted by 189 Member States at the United Nations Special Session on Children in May 2002. Both of these commitments build upon promises made by the international community at the 1990 World Summit for Children.
The Selected Districts of West Papua Province MICS 2011 was designed to collect information across a broad number of social indicators covering education, environment, health and child protection. The sample was selected in two stages. Within each district, a specified number of census enumeration areas were selected systematically with probability proportional to size. After a household listing was carried out within the selected enumeration areas, a systematic sample of 25 households was drawn in each sample enumeration area. The sample is not self-weighting and sample weights are used.
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, child labour and child discipline.
- Women: woman's background, child mortality, desire for last birth, maternal and newborn health, contraception, unmet need, attitudes toward domestic violence, marriage/union, sexual behavior, HIV/AIDS, and alcohol use.
- Children: child's age, birth registration, breastfeeding, malaria, and immunization.
- Men: man's background, attitudes toward domestic violence, marriage/union, sexual behavior, HIV/AIDS, circumcision and alcohol use.
Selected Districts of West Papua Province: Kaimana, Manokwari and Sorong
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 15-49 years.
Producers and sponsors
United Nations Children’s Fund
Badan Pusat Statistik (Statistics Indonesia)
United Nations Children’s Fund
Financial and technical support
National Development Planning Agency
Ministry of Home Affairs
The primary objective of the sample design for the West Papua Multiple Indicator Cluster Survey was to produce statistically reliable district level estimates of most indicators, in three selected districts (Kaimana, Manokwari and Sorong districts) of West Papua Province, for urban and rural areas. The districts were selected purposively by considering topographic areas in West Papua Province.
A two-stage, stratified cluster sampling approach was used for the selection of the survey sample.
The target sample size for the West Papua MICS was calculated as 1,000 households for each selected district.
The resulting number of households from this exercise was 1,000 households per selected district which is the sample size needed in each districts-thus yielding about 3,000 in total in the three districts of West Papua Province. The average number of households selected per cluster for each selected district was determined as 25 households, based on a number of considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of sample households per cluster, it was calculated that 40 sample clusters would need to be selected in each selected district.
Since a two-stage, stratified cluster sampling approach was used for the selection of the survey sample, two sampling frames were used for each stage.
- For the first stage, the recent master list of Census Blocks, dated 5 May 2010. The list is complemented with the information on the number of household resulted from listing of 2010 population census, number of HH in each block census, information on the difficulty of the area, and urban/rural classification. Forty census blocks were selected according to probability proportional to size (pps), while the size is number of households in each districts based on the listing of 2010 Population Census.
- For the second stage, a list of households from an updated listing of 2010 Population Census. Twenty-five households in each block census were selected using systematic random sampling.
Since the sampling frame (the 2010 Population Census) was not up-to-date, a listing of households was conducted in each cluster by all enumeration teams to up-date the existing information based on Population Census in all the sample enumeration areas prior to the selection of households.
Lists of households were prepared by the enumeration team in the field for each enumeration area. The households were then sequentially numbered from 1 to n (the total number of households in each enumeration area) at the Central Statistical Office, where the selection of 25 households in each enumeration area was carried out by the supervisor using random systematic selection procedures.
The sampling procedures are more fully described in "Multiple Indicator Cluster Survey 2011 - Final Report" pp.159-161.
Of the 2,913 households selected for the three districts sample, 2,843 were found to be occupied. Of these, 2,816 were successfully interviewed for a household response rate of 99.1 percent. In the interviewed households, 2,853 women (age 15-49 years) were identified. Of these, 2,715 were successfully interviewed, yielding a response rate of 95.2 percent within interviewed households. In addition, 2,917 men (age 15-49 years) were listed in the household questionnaire. Questionnaires were completed for 2,736 of eligible men, a response rate of 93.8 percent within interviewed households. There were 1,394 children under age five listed in the household questionnaire. Questionnaires were completed for 1,354 of these children, a response rate of 97.1 percent within interviewed households. Overall response rates of 94.3, 92.9 and 96.2 are calculated for the women’s, men’s and under-5’s interviews respectively.
The household response rate was similar among the three districts of Kaimana, Manokwari and Sorong, whereas the women, men and children response rates were generally lower in the district of Manokwari.
The West Papua Multiple Indicator Cluster Survey sample is not self-weighting. Essentially, by allocating equal numbers of households to each of the regions, different sampling fractions were used in each region since the size of the regions varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data.
The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling stratum (h) and PSU (i).
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 updated listing were different, individual sampling fractions for households in each sample enumeration area (cluster) were calculated. The sampling fractions for households in each enumeration area (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 varied between 0.188711 and 3.175026 in the 120 sample enumeration areas (clusters).
Sample weights were appended to all data sets and analyses were performed by weighting each household, woman, men or under-5 with these sample weights.
Dates of Data Collection
Data Collection Mode
There is one supervisor for each of the 4 data collection teams in the field.
Data Collection Notes
Training of trainers for the field was conduct for 12 days during 4-15 July 2011 in Bogor. Enumerators training was conducted in Jayapura for 15 days during 19 September - 3 October 2011. Training included lectures on interviewing techniques and the contents of the questionnaires, and mock interviews between trainees to gain practice in asking questions. Towards the end of the training period, trainees spent one and a half days in practice interviewing in Manokwari District.
The data were collected by four teams; each was comprised of four interviewers, one editor, and a supervisor. Fieldwork began in 5 October 2011 and concluded in 5 December 2011.
Badan Pusat Statistik (Statistics Indonesia)
The questionnaires for the Generic MICS were structured questionnaires based on the MICS4 model questionnaire with some modifications and additions. Household questionnaires were administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes household listing form, education, water and sanitation, household characteristics, insecticide-treated nets, child labour and child discipline.
In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49, children under age five and men age 15-49. For children, the questionnaire was administered to the mother or primary caretaker of the child.
The women's questionnaire includes woman's background, child mortality, desire for last birth, maternal and newborn health, contraception, unmet need, attitudes toward domestic violence, marriage/union, sexual behavior, HIV/AIDS, and alcohol use.
The children's questionnaire includes child's age, birth registration, breastfeeding, malaria, and immunization.
The men's questionnaire includes man's background, attitudes toward domestic violence, marriage/union, sexual behavior, HIV/AIDS, circumcision and alcohol use.
The questionnaires are based on the MICS4 model questionnaire. From the MICS4 model English version, the questionnaires were translated into Bahasa Indonesia and were pre-tested in Kemtuk Village in Jayapura District and Bagai Village in Keerom District in Papua Province during 18-22 July 2011. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.
Data was entered using the CSPro software. The data was entered on 12 microcomputers and carried out by 12 data entry operators, under the supervision of one secondary editor 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 MICS4 programme and adapted to the Selected Districts of West Papua Province MICS questionnaire were used throughout. Data processing began simultaneously with data collection in 8 October 2011 and was completed in 31 December 2011. Data was analysed using the Statistical Package for Social Sciences (SPSS) software programme, Version 18, and the model syntax and tabulation plans developed by UNICEF were used for this purpose.
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 an 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 per cent of all possible samples of identical size and design.
For the calculation of sampling errors from MICS data, 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 for each district: Kaimana, Manokwari and Sorong. Seven are based on household members, 11 are based on women, 7 are based on men and 10 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 eligible and interviewed men
- Age distribution of children under 5 in household and children under 5 questionnaires
- Women’s completion rates by socio-economic characteristics of households
- Men’s completion rates by socio-economic characteristics of households
- Completion rates for under-5 questionnaires by socio-economic characteristics of households
- Completeness of reporting
- Observation of bednets
- Observation of women’s health cards
- Observation of under-5s 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
- Sex ratio at birth among children ever born and living
The results of each of these data quality tables are shown in appendix C in document "Multiple Indicator Cluster Survey 2011 - Final Report" pp.167-177.
BPS Statistics Indonesia
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United Nations Children’s Fund, Badan Pusat Statistik (Statistics Indonesia). Indonesia Multiple Indicator Cluster Survey (MICS) 2011 - Selected Districts of West Papua, Ref. IDN_2011_MICS-SDWP_v01_M. Dataset downloaded from [url] on [date].
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