Multiple Indicator Cluster Survey 2003
Afghanistan, 2003
Reference ID
AFG_2003_MICS_v01_M
Producer(s)
Central Statistics Office
Created on
Sep 29, 2011
Last modified
Mar 29, 2019
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16055
Downloads
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Identification
Survey ID Number
AFG_2003_MICS_v01_M
Title
Multiple Indicator Cluster Survey 2003
Country
| Name | Country code |
|---|---|
| Afghanistan | AFG |
Study type
Multiple Indicator Cluster Survey - Round 2 [hh/mics-2]
Series Information
A first MICS survey was conducted in Afghanistan in 2000.
Kind of Data
Sample survey data [ssd]
Scope
Notes
The scope of Afganistan MICS 2003 includes:
HOUSEHOLD MEMBER LISTING
- Demographic information
- Economic activity
- Education
CHILDREN
- Vaccination
- Vitamin A
- Health
- Breastfeeding
- Education
- Child labor
WOMEN
- Fertility
- Family planning
- Delivery
- Pre-natal care
HOUSE
- Housing characteristics
HOUSEHOLD MEMBER LISTING
- Demographic information
- Economic activity
- Education
CHILDREN
- Vaccination
- Vitamin A
- Health
- Breastfeeding
- Education
- Child labor
WOMEN
- Fertility
- Family planning
- Delivery
- Pre-natal care
HOUSE
- Housing characteristics
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Central Statistics Office | Afghanistan Transitional Authority |
Producers
| Name |
|---|
| United Nations Children Fund |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| United Nations Children Fund | UNICEF |
Sampling
Sampling Procedure
Sampling Frame
Availability of a sampling frame was a major constraint in planning the survey. There were two sources of data as sampling frame, one is the Population Census-1979 data from Central Statistics Office (CSO) and the other was the National Immunization Day (NID) coverage data from the WHO and UNICEF. Both the sources have their own limitations and advantages. Census 1979 data are outdated with all the displacement due to war and fertility and mortality. However, the data were found organized for use in any purpose. On the other hand, the NID data were produced based on the NID coverage in every round, which could be considered as the most recent. But the areas with incomplete coverage will have faulty data because the number beyond the coverage is not known accurately. The format of the data in NID was also not standardized for all the provinces. Standardization would need sometime to make it user-friendly. A comparative analysis was carried out to address the sampling frame issue and it was apparent that Census data could be used for the purpose at the moment. A sampling design and the related survey methodology was henceforth developed for MICS in Afghanistan in 2003.
Sample Design
A two-stage cluster sampling strategy was decided for the survey where villages were treated as the primary sampling unit (PSU). The number of PSUs selected from each province is decided as 20. This again translates to a number of 27.5 households per PSU or cluster. Clusters were defined as the compact area segment of 55 households in each selected PSU.
The six major cities were treated as separate domain of the study. Hence they were separated out from the respective provinces. For each of these cities, except Kabul, 20 clusters are selected while the number is 25 for Kabul city. Under consideration of huge population and possible heterogeneity, this number is proposed for Kabul to achieve wider/better coverage.
Selection of Households
Every selected village was partitioned into several equal segments of roughly 55 households each. Segments were numbered according to a prescribed fashion, starting from southeast corner and move anti-clockwise. And the segment corresponding to the random number of the selection was selected for survey. Within each segment every alternative households were interviewed starting randomly from the 1st or 2nd household.
Stratification and post-stratification
Stratification for the survey is decided to be at two levels
1. 32 provinces as both strata and study domain, where 6 provinces containing the major cities had only the rural areas
2. 6 major cities as strata and study domain
3. Post-stratification was done for the 26 provinces where urban and rural areas were not separated at the time of sampling. This post stratification is used to separate out the data of the provincial urban areas (defined as the district of provincial head quarter) from that of rural areas.
Hence the estimates are available for
1. All 32 provinces (urban +rural)
2. 6 rural provinces, 6 major cities
3. National Metro cities, other urban areas (26 provincial towns) and
4. National Urban, National Rural, National (Urban+Rural)
Availability of a sampling frame was a major constraint in planning the survey. There were two sources of data as sampling frame, one is the Population Census-1979 data from Central Statistics Office (CSO) and the other was the National Immunization Day (NID) coverage data from the WHO and UNICEF. Both the sources have their own limitations and advantages. Census 1979 data are outdated with all the displacement due to war and fertility and mortality. However, the data were found organized for use in any purpose. On the other hand, the NID data were produced based on the NID coverage in every round, which could be considered as the most recent. But the areas with incomplete coverage will have faulty data because the number beyond the coverage is not known accurately. The format of the data in NID was also not standardized for all the provinces. Standardization would need sometime to make it user-friendly. A comparative analysis was carried out to address the sampling frame issue and it was apparent that Census data could be used for the purpose at the moment. A sampling design and the related survey methodology was henceforth developed for MICS in Afghanistan in 2003.
Sample Design
A two-stage cluster sampling strategy was decided for the survey where villages were treated as the primary sampling unit (PSU). The number of PSUs selected from each province is decided as 20. This again translates to a number of 27.5 households per PSU or cluster. Clusters were defined as the compact area segment of 55 households in each selected PSU.
The six major cities were treated as separate domain of the study. Hence they were separated out from the respective provinces. For each of these cities, except Kabul, 20 clusters are selected while the number is 25 for Kabul city. Under consideration of huge population and possible heterogeneity, this number is proposed for Kabul to achieve wider/better coverage.
Selection of Households
Every selected village was partitioned into several equal segments of roughly 55 households each. Segments were numbered according to a prescribed fashion, starting from southeast corner and move anti-clockwise. And the segment corresponding to the random number of the selection was selected for survey. Within each segment every alternative households were interviewed starting randomly from the 1st or 2nd household.
Stratification and post-stratification
Stratification for the survey is decided to be at two levels
1. 32 provinces as both strata and study domain, where 6 provinces containing the major cities had only the rural areas
2. 6 major cities as strata and study domain
3. Post-stratification was done for the 26 provinces where urban and rural areas were not separated at the time of sampling. This post stratification is used to separate out the data of the provincial urban areas (defined as the district of provincial head quarter) from that of rural areas.
Hence the estimates are available for
1. All 32 provinces (urban +rural)
2. 6 rural provinces, 6 major cities
3. National Metro cities, other urban areas (26 provincial towns) and
4. National Urban, National Rural, National (Urban+Rural)
Response Rate
Non-response rate differs for different questions due to different factors like memory lapse, counting problems and understanding of the questions. However, the rate of non-response including inconsistent response which also treated as non-response during editing operation was mostly 2-3% in different questions. Again, only the month and year were assessed as the date of birth of the children.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2003 | 2003 |
Data Collection Mode
Face-to-face [f2f]
Supervision
Quality control
In each zone with 4/5 provinces and a city, there were some Quality Control Officers (QCOs). They were from CSO staff member and hired by UNICEF as trainers. One Bangladeshi QCO was employed in each of six UNICEF zone offices to support the local QCOs (Bangladeshi QCOs participated month-long field testing of questionnaire in Bangladesh and also participated training at the zones with locals). A standard guideline was prepared for the quality control of the field data collection, and an additional training was arranged for them.
In each zone with 4/5 provinces and a city, there were some Quality Control Officers (QCOs). They were from CSO staff member and hired by UNICEF as trainers. One Bangladeshi QCO was employed in each of six UNICEF zone offices to support the local QCOs (Bangladeshi QCOs participated month-long field testing of questionnaire in Bangladesh and also participated training at the zones with locals). A standard guideline was prepared for the quality control of the field data collection, and an additional training was arranged for them.
Data Collection Notes
Field team
There was two teams for each province and major city for data collection. Each team had one supervisor and two pairs of enumerators (male and female with some socially acceptable relationship). In each cluster, they spent one day for listing operation and two days to collect data from 28 households on an average.
Recruitment of Field Personnel
Unicef zonal offices recruited the field staff through some NGOs at local level. They are mostly from the different national institutions like universities, schools, health centres and other local bodies etc. One Unicef staff member at each zonal office was the focal point for this survey.
There was two teams for each province and major city for data collection. Each team had one supervisor and two pairs of enumerators (male and female with some socially acceptable relationship). In each cluster, they spent one day for listing operation and two days to collect data from 28 households on an average.
Recruitment of Field Personnel
Unicef zonal offices recruited the field staff through some NGOs at local level. They are mostly from the different national institutions like universities, schools, health centres and other local bodies etc. One Unicef staff member at each zonal office was the focal point for this survey.
Data Processing
Data Editing
Editing and coding: About 13 people were recruited at CSO for the editing and coding at central level. Immediately after data collection started, they were imparted a hands-on training on editing and coding. By the time some data reached the HQ from field they started their work. Two edit-verifiers crosschecked coded questionnaires. Two internationals supervised the whole work and crosschecked some randomly selected filled-in questionnaires.
Data entry and Checking: A data entry software was developed in MS-ACCESS by the consultant group which was user-friendly while for each question the range checks, internal consistency checks and non-response checks were also in-built to prevent wrong entry.
A total of 11 people at CSO and 8 people at UNICEF were recruited for the data entry at Kabul. 11 computers and a power generator were installed for the purpose at CSO and 6 computers at UNICEF. Two data entry supervisors (Bangladeshi) supervised the work. They also crosschecked the entered data on random basis.
Data entry and Checking: A data entry software was developed in MS-ACCESS by the consultant group which was user-friendly while for each question the range checks, internal consistency checks and non-response checks were also in-built to prevent wrong entry.
A total of 11 people at CSO and 8 people at UNICEF were recruited for the data entry at Kabul. 11 computers and a power generator were installed for the purpose at CSO and 6 computers at UNICEF. Two data entry supervisors (Bangladeshi) supervised the work. They also crosschecked the entered data on random basis.
Access policy
Contacts
Confidentiality
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.
Access conditions
Survey datasets are distributed at no cost for legitimate research.
Interested users are requested to provide an e-mail address, their name, affiliation and type of institution and country of residence. A short description of the
objectives of the research project must also be provided
Users who download the data agree to provide UNICEF with copies of all reports and publications based on the requested data.
The data may not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of UNICEF.
No attempt will be made to re-identify respondents, and no use will be made of the identity of any person discovered inadvertently. Any such discovery would
immediately be reported to UNICEF.
Email: mics@unicef.org <mailto:mics@unicef.org>
Global MICS Coordinator
Statistics and Monitoring
Division of Policy and Practice
UNICEF
Three United Nations Plaza
New York, NY 10017
USA
Requests for access to the datasets should be made through the website: http://www.childinfo.org.
Interested users are requested to provide an e-mail address, their name, affiliation and type of institution and country of residence. A short description of the
objectives of the research project must also be provided
Users who download the data agree to provide UNICEF with copies of all reports and publications based on the requested data.
The data may not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of UNICEF.
No attempt will be made to re-identify respondents, and no use will be made of the identity of any person discovered inadvertently. Any such discovery would
immediately be reported to UNICEF.
Email: mics@unicef.org <mailto:mics@unicef.org>
Global MICS Coordinator
Statistics and Monitoring
Division of Policy and Practice
UNICEF
Three United Nations Plaza
New York, NY 10017
USA
Requests for access to the datasets should be made through the website: http://www.childinfo.org.
Citation requirements
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 of the data files (for datasets obtained on-line)
- 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 of the data files (for datasets obtained on-line)
Disclaimer and copyrights
Disclaimer
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.
Metadata production
DDI Document ID
DDI_WB_AFG_2003_MICS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | World Bank | Documentation of the DDI |
DDI Document version
Version 01 (September 2011)