Multiple Indicator Cluster Survey 2005, Monitoring the situation of children and women
Serbia, 2005 - 2006
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Reference ID
SRB_2005_MICS_v01_M
Producer(s)
UNICEF Belgrade, MICS3 Global Team, SORS, SMMRI
Collection(s)
Created on
Mar 22, 2011
Last modified
Sep 26, 2013
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Identification
Survey ID Number
SRB_2005_MICS_v01_M
Title
Multiple Indicator Cluster Survey 2005, Monitoring the situation of children and women
Subtitle
Monitoring the situation of children and women
Translated Title
Istraživanje višestrukih pokazatelja stanja žena i dece, Srbija, 2005
Country/Economy
| Name | Country code |
|---|---|
| Serbia | SRB |
Study type
Multiple Indicator Cluster Survey - Round 3 [hh/mics-3]
Series Information
The Multiple Indicator Cluster Survey, Round 3 (MICS3) is the third round of MICS surveys, previously conducted in 1996 (MICS1) and 2000 (MICS2). Many questions and indicators are consistent and compatible with the prior round of MICS (MICS2) but less so with MICS1, although there have been a number of changes in definition of indicators between rounds. Details can be found by reviewing the indicator definitions.
Abstract
The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular.
MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.
Survey Objectives
The 2005 Serbia Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Serbia.
- To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, 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 Serbia and to strengthen technical expertise in the design, implementation, and analysis of such systems.
Survey Content
MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.
Survey Implementation
The survey was carried out by the Statistical Office of the Republic of Serbia and the Strategic Marketing Research Agency, 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, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.
In 2005 Serbia and Montenegro was the State Union composed of the Republic of Serbia (92.5% of population) and the Republic of Montenegro (7.5% of total population). The MICS 2005 survey was planned and implemented on the whole territory of Serbia and Montenegro, and all documents regarding survey plan and contracts with implementing agencies covered the State Union. In May, 2006 the Republic of Montenegro had a referendum of independency and the State Union broke apart. The results of MICS 2005 survey were presented separately for both countries and two separate reports were prepared.
The survey was implemented by the Statistical Office of the Republic of Serbia (in Serbia) and the Statistical Office of the Republic of Montenegro (in Montenegro) and the expert research agency - Strategic Marketing & Media Research Institute (SMMRI), which covered the survey implementation in both Serbia and Montenegro.
Special tasks performed by the Statistical Office of the Republic of Serbia: Preparation of questionnaire for the survey: Preparation of methodological guidelines for realization of the survey; Updating of lists of households in the selected census block units; Conducting the pilot ; Selection of households to be covered by sample; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Special tasks performed by the SMMRI: Sample selection; Preparation of survey tools; Organising the training; Conducting the pilot; Updating of lists of households in the selected census block units; Organising field work; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Data processing and analysis; Preparation of report.
MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.
Survey Objectives
The 2005 Serbia Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Serbia.
- To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, 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 Serbia and to strengthen technical expertise in the design, implementation, and analysis of such systems.
Survey Content
MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.
Survey Implementation
The survey was carried out by the Statistical Office of the Republic of Serbia and the Strategic Marketing Research Agency, 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, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.
In 2005 Serbia and Montenegro was the State Union composed of the Republic of Serbia (92.5% of population) and the Republic of Montenegro (7.5% of total population). The MICS 2005 survey was planned and implemented on the whole territory of Serbia and Montenegro, and all documents regarding survey plan and contracts with implementing agencies covered the State Union. In May, 2006 the Republic of Montenegro had a referendum of independency and the State Union broke apart. The results of MICS 2005 survey were presented separately for both countries and two separate reports were prepared.
The survey was implemented by the Statistical Office of the Republic of Serbia (in Serbia) and the Statistical Office of the Republic of Montenegro (in Montenegro) and the expert research agency - Strategic Marketing & Media Research Institute (SMMRI), which covered the survey implementation in both Serbia and Montenegro.
Special tasks performed by the Statistical Office of the Republic of Serbia: Preparation of questionnaire for the survey: Preparation of methodological guidelines for realization of the survey; Updating of lists of households in the selected census block units; Conducting the pilot ; Selection of households to be covered by sample; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Special tasks performed by the SMMRI: Sample selection; Preparation of survey tools; Organising the training; Conducting the pilot; Updating of lists of households in the selected census block units; Organising field work; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Data processing and analysis; Preparation of report.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households (defined as a group of persons who usually live and eat together)
De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)
Women aged 15-49
Children aged 0-4
De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)
Women aged 15-49
Children aged 0-4
Version
Version Description
Version 1.0: Edited data used for final report
Version Date
2007-11-11
Scope
Notes
The scope of the Multiple Indicator Cluster Survey includes:
HOUSEHOLD: Household listing, Education, Water and Sanitation, Household characteristics, Child labour, Child Discipline, Child Disability, and Roma in Roma settlements.
WOMEN: Women's characteristics, Child Mortality (this module was used only in Roma households living in Roma settlements), Maternal and Newborn Health, Security of tenure on eviction for the Woman, Marriage/Union, Contraception, Attitudes toward domestic violence, Sexual behaviour, and HIV/AIDS.
CHILDREN: Children's characteristics, Birth Registration and Early Learning, Child Development, Breastfeeding, Care of Illness, Immunization, and Anthropometry.
HOUSEHOLD: Household listing, Education, Water and Sanitation, Household characteristics, Child labour, Child Discipline, Child Disability, and Roma in Roma settlements.
WOMEN: Women's characteristics, Child Mortality (this module was used only in Roma households living in Roma settlements), Maternal and Newborn Health, Security of tenure on eviction for the Woman, Marriage/Union, Contraception, Attitudes toward domestic violence, Sexual behaviour, and HIV/AIDS.
CHILDREN: Children's characteristics, Birth Registration and Early Learning, Child Development, Breastfeeding, Care of Illness, Immunization, and Anthropometry.
Topics
| Topic | Vocabulary |
|---|---|
| Household members | MICS Topics |
| Education | MICS Topics |
| Water and sanitation | MICS Topics |
| Household characteristics | MICS Topics |
| Durability of housing | MICS Topics |
| Security of tenure | MICS Topics |
| Child labour | MICS Topics |
| Child discipline | MICS Topics |
| Child disability | MICS Topics |
| Roma in Roma settlements | MICS Topics |
| Women's background | MICS Topics |
| Child mortality (Roma in Roma settlemets only) | MICS Topics |
| Maternal and newborn health | MICS Topics |
| Security of tenure on eviction for the Woman | MICS Topics |
| Marriage and union | MICS Topics |
| Contraception | MICS Topics |
| Attitudes towards domestic violence | MICS Topics |
| HIV/AIDS | MICS Topics |
| Sexual behaviour | MICS Topics |
| Children's background | MICS Topics |
| Birth registration | MICS Topics |
| Early learning | MICS Topics |
| Child development | MICS Topics |
| Breastfeeding | MICS Topics |
| Care of illness | MICS Topics |
| Immunization | MICS Topics |
| Anthropometry | MICS Topics |
Coverage
Geographic Coverage
The sample for the Serbia Multiple Indicator Cluster Survey (MICS) 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 for six regions: Vojvodina, Belgrade, West, Central, East and South-East Serbia. Belgrade has a large population (almost one-quarter of the total) and its predominantly urban characteristics make it necessary to separate it from the rest of Central Serbia, to which it administratively belongs. In order to look more deeply into existing ethnic disparities and to provide national estimates, a separate sample was designed for Roma living in Roma settlements.
Universe
The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| UNICEF Belgrade | United Nations Childrens Funds Belgrade |
| MICS3 Global Team | United Nations Childrens Funds NYHQ |
| SORS | Statistical Office of Republic of Serbia |
| SMMRI | Strategic Marketing |
Producers
| Name | Affiliation | Role |
|---|---|---|
| UNICEF Belgrade | United Nations Childrens Founds | Technical and financial support, supervision |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| UNICEF HQ | UNICEF | Funding of survey implementation |
| Canadian Government | Donations | |
| SIDA | SIDA | Donations |
| Organisation for economic co-operation and development | OECD | Financial and technical support in data archiving |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Ivana Bjelic | SMMRI | Technical implementation in all phases |
| Dragisa Bjeloglav | SMMRI | National coordinator |
| Trevor Croft | UNICEF | Conceptualization and design of MICS survey |
| Ngagne Diakhate | UNICEF | On-line technical support on data processing and analysis |
| Dragana Djokovic-Papic | SORS | SORS team leader |
| Attila Hancioglu | UNICEF | Conceptualization and design of MICS survey, overall cordination |
| Emma Holmberg | UNICEF | On-line technical support on data processing and analysis |
| Eldiberto Loaiza | UNICEF | Conceptualization and design of MICS survey |
| Oliver Petrovic | UNICEF Belgrade | Overall coordination |
| George Sakvarelidze | UNICEF | Regional coordination |
| Marco Segone | UNICEF | Conceptualization and design of MICS survey |
| Ann-Lis Svensson | UNICEF | Inclusion of the most exluded population group in the survey design |
| Dragan Vukmirovic | SORS | SORS director |
| Tessa Wardlaw | UNICEF | Conceptualization and design of MICS survey |
Sampling
Sampling Procedure
The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2005 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.
The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to prodvide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. In additon, the sample was designed to provide estimates for each of the 6 regions (Vojvodina, Belgrade, West, Central, East and South-East Serbia) for key indicators. Separate sample was designed for Roma living in Roma settlements.
Important factors which influenced the sample design of both Serb and Roma samples are the fertility rate and number of household members.
A stratified, two-stage random sampling approach was used for the selection of the survey sample.
In the case of the Serbia without the Roma settlements sample, 400 census enumeration areas within each region with probability proportional to size were selected during the first stage. Since the sample frame (Census 2002) was not up to date, household lists in all selected enumeration areas were updated prior to the selection of households. Owing to the low fertility rate and small household size, households were stratified into two categories. One category of households consists of households with under 5 children, while the other category consists of households without children under 5. The allocation of the sample in the category of households with children was significantly greater than the allocation of the sample in the category of households without children. Based on the updated information, selected units were divided into clusters of 18 households on average, plus 3 backup households. Backup households were interviewed only if some of the first 18 households were not found. In the event that a household refused to be interviewed, a backup household was not contacted. In each cluster, the number of households with children was selected with probability proportional to size.
In the case of the Roma population, the universe could be defined only for Roma who live in separate settlements. During the first stage, 106 census enumeration areas were selected. The updating of household lists was done prior to household selection, but there was no need for sample stratification of households with and without children under 5. The average number of households selected in each cluster was 18 on average, plus 3 backup households.
Secondly, after the household listing was carried out within the selected enumeration areas, a systematic sample of 7,794 households in Serbia without Roma from Roma settlements and 1,959 Roma households was drawn up, which makes a total of 9,953 sampled households.
The 2002 Serbian Population Census framework was used for the selection of clusters. Census enumeration areas (app. 100 households) were defined as primary sampling units (PSUs), and were selected from each of the sampling domains by using systematic pps (probability proportional to size) sampling procedures, based on the estimated sizes of the enumeration areas from the 2002 Population Census. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the 6 regions by urban and rural areas separately.
Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.
The Serbia Multiple Indicator Cluster Survey sample is not self-weighted. For reporting of national level results, sample weights were used, according to MICS standard procedures.
The sampling procedures are more fully described in the sampling design document and the sampling appendix of the final report.
The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to prodvide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. In additon, the sample was designed to provide estimates for each of the 6 regions (Vojvodina, Belgrade, West, Central, East and South-East Serbia) for key indicators. Separate sample was designed for Roma living in Roma settlements.
Important factors which influenced the sample design of both Serb and Roma samples are the fertility rate and number of household members.
A stratified, two-stage random sampling approach was used for the selection of the survey sample.
In the case of the Serbia without the Roma settlements sample, 400 census enumeration areas within each region with probability proportional to size were selected during the first stage. Since the sample frame (Census 2002) was not up to date, household lists in all selected enumeration areas were updated prior to the selection of households. Owing to the low fertility rate and small household size, households were stratified into two categories. One category of households consists of households with under 5 children, while the other category consists of households without children under 5. The allocation of the sample in the category of households with children was significantly greater than the allocation of the sample in the category of households without children. Based on the updated information, selected units were divided into clusters of 18 households on average, plus 3 backup households. Backup households were interviewed only if some of the first 18 households were not found. In the event that a household refused to be interviewed, a backup household was not contacted. In each cluster, the number of households with children was selected with probability proportional to size.
In the case of the Roma population, the universe could be defined only for Roma who live in separate settlements. During the first stage, 106 census enumeration areas were selected. The updating of household lists was done prior to household selection, but there was no need for sample stratification of households with and without children under 5. The average number of households selected in each cluster was 18 on average, plus 3 backup households.
Secondly, after the household listing was carried out within the selected enumeration areas, a systematic sample of 7,794 households in Serbia without Roma from Roma settlements and 1,959 Roma households was drawn up, which makes a total of 9,953 sampled households.
The 2002 Serbian Population Census framework was used for the selection of clusters. Census enumeration areas (app. 100 households) were defined as primary sampling units (PSUs), and were selected from each of the sampling domains by using systematic pps (probability proportional to size) sampling procedures, based on the estimated sizes of the enumeration areas from the 2002 Population Census. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the 6 regions by urban and rural areas separately.
Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.
The Serbia Multiple Indicator Cluster Survey sample is not self-weighted. For reporting of national level results, sample weights were used, according to MICS standard procedures.
The sampling procedures are more fully described in the sampling design document and the sampling appendix of the final report.
Deviations from the Sample Design
No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.
Response Rate
Of the 9.953 households selected for the sample, 9.372 were found to be occupied. Of these, 8.730 were successfully interviewed for a household response rate of 93 percent. In the interviewed households, 7.895 women (aged 15-49) were identified. Of these, 7.516 were successfully interviewed, yielding a response rate of 95 percent. In addition, 3.838 children under the age of five were listed in the household questionnaire. Questionnaires were completed for 3.777 of these children, which corresponds to a response rate of 98 percent. Overall response rates of 89 and 92 percent are calculated for the women's and under-5s' interviews respectively.
Weighting
Sample weights were calculated for each of the datafiles.
Sample weights for the household data were computed as the inverse of the probability of selection of the household, computed at the sampling domain level (urban/rural within each region). The household weights were adjusted for non-response at the domain level, and were then normalized by a constant factor so that the total weighted number of households equals the total unweighted number of households.
Sample weights for the women's data used the un-normalized household weights, adjusted for non-response for the women's questionnaire, and were then normalized by a constant factor so that the total weighted number of women's cases equals the total unweighted number of women's cases.
Sample weights for the children's data followed the same approach as the women's and used the un-normalized household weights, adjusted for non-response for the children's questionnaire, and were then normalized by a constant factor so that the total weighted number of children's cases equals the total unweighted number of children's cases.
For merged Serbia and Roma samples, additional customisation of calculated weights was performed. Since according to the 2002 Census, the proportion of Roma households in the total Serbia household population is 1 percent, the proportion of women aged 15 to 49 is 1.3 percent and the proportion of children under 5 is 3.4 percent; the final weights are products of normalised weights and the ratio of proportion of both the Roma and non-Roma population.
The household weight variable is called HHWEIGHT and is used with the household data. Same weight is applied to the household listiong data, but under name HLWEIGHT. Women and children weights are called WMWEIGHT and CHWEIGHT and are used in women and children data, respectively.
Sample weights for the household data were computed as the inverse of the probability of selection of the household, computed at the sampling domain level (urban/rural within each region). The household weights were adjusted for non-response at the domain level, and were then normalized by a constant factor so that the total weighted number of households equals the total unweighted number of households.
Sample weights for the women's data used the un-normalized household weights, adjusted for non-response for the women's questionnaire, and were then normalized by a constant factor so that the total weighted number of women's cases equals the total unweighted number of women's cases.
Sample weights for the children's data followed the same approach as the women's and used the un-normalized household weights, adjusted for non-response for the children's questionnaire, and were then normalized by a constant factor so that the total weighted number of children's cases equals the total unweighted number of children's cases.
For merged Serbia and Roma samples, additional customisation of calculated weights was performed. Since according to the 2002 Census, the proportion of Roma households in the total Serbia household population is 1 percent, the proportion of women aged 15 to 49 is 1.3 percent and the proportion of children under 5 is 3.4 percent; the final weights are products of normalised weights and the ratio of proportion of both the Roma and non-Roma population.
The household weight variable is called HHWEIGHT and is used with the household data. Same weight is applied to the household listiong data, but under name HLWEIGHT. Women and children weights are called WMWEIGHT and CHWEIGHT and are used in women and children data, respectively.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2005-10-01 | 2006-01-10 |
Data Collection Mode
Face-to-face [f2f]
Supervision
The data was collected by 47 teams; each comprised of two interviewers, one driver and one editor/measurer. 18 supervisors were in charge for field-work supervision. The whole process was aditionaly monitored by 7 field editors. Each teams used a 4 wheel dirve vehicle to travel from cluster to cluster (and where necessary within cluster).
The role of the supervisor was to coordinate field data collection activities, including management of the field teams, supplies and equipment, finances, maps and listings, coordinate with local authorities concerning the survey plan and make arrangements for accomodation and travel. Additionally, the field supervisor assigned the work to the interviewers, spot checked work, maintained field control documents, and sent completed questionnaires and progress reports to the central office.
The field editor was responsible for reviewing each questionnaire at the end of the day, checking for missed questions, skip errors, fields incorrectly completed, and checking for inconsistencies in the data. The field editor also observed interviews and conducted review sessions with interviewers.
Responsibilities of the supervisors and field editors are described in the Instructions for Supervisors and Field Editors, together with the different field controls that were in place to control the quality of the fieldwork.
Field visits were also made by a team of central staff on a periodic basis during fieldwork. The senior staff of UNICEF Belgrade also made 3 visits to field teams to provide support and to review progress.
The role of the supervisor was to coordinate field data collection activities, including management of the field teams, supplies and equipment, finances, maps and listings, coordinate with local authorities concerning the survey plan and make arrangements for accomodation and travel. Additionally, the field supervisor assigned the work to the interviewers, spot checked work, maintained field control documents, and sent completed questionnaires and progress reports to the central office.
The field editor was responsible for reviewing each questionnaire at the end of the day, checking for missed questions, skip errors, fields incorrectly completed, and checking for inconsistencies in the data. The field editor also observed interviews and conducted review sessions with interviewers.
Responsibilities of the supervisors and field editors are described in the Instructions for Supervisors and Field Editors, together with the different field controls that were in place to control the quality of the fieldwork.
Field visits were also made by a team of central staff on a periodic basis during fieldwork. The senior staff of UNICEF Belgrade also made 3 visits to field teams to provide support and to review progress.
Data Collection Notes
The Statistical Office of the Republic of Serbia and The Strategic Marketing Research Agency were responsible for data collection. The whole territory of Serbia was divided into 18 districts according to the regional network of responsible institutions. In each district a team of people was selected - one supervisor for the district and the interviewers (whose number depended on the number of clusters in the region).
Training of supervisors was conducted in September 2005, before the pre-test. Towards the end of the supervisor training period, supervisors spent five days in practice interviewing and checking questionnaires and methodology in several places: Belgrade, Novi Sad, Subotica, Kraljevo, Kragujevac, Valjevo and Nis.
The data was collected by 47 teams; each comprised of two interviewers, one driver and one editor/measurer. Each team in charge of data collection in Roma settlements included one or two members from the Roma women's network, and one professional interviewer. One supervisor was in charge of two or three teams. Fieldwork began in October 2005 and concluded in January 2006. Interviewing took place everyday throughout the fieldwork period, although interviewing teams were permitted to take one day off per week.
Interviews averaged 35 minutes for the household questionnaire , 30 minutes for the women's questionnaire, and 25 for the under five children's questionnaire (excluding the anthropometry). Interviews were conducted primarily in Serbian, but they were translated into Albanian and Hungarian and these translated questionnaires were used when the respondent did not speak Serbian.
The overall field coordinators were: Natalija Biliskov, Dragana Djokovic Papic, Ljiljana Djordjevic and Tatjana Jovanov.
Training of supervisors was conducted in September 2005, before the pre-test. Towards the end of the supervisor training period, supervisors spent five days in practice interviewing and checking questionnaires and methodology in several places: Belgrade, Novi Sad, Subotica, Kraljevo, Kragujevac, Valjevo and Nis.
The data was collected by 47 teams; each comprised of two interviewers, one driver and one editor/measurer. Each team in charge of data collection in Roma settlements included one or two members from the Roma women's network, and one professional interviewer. One supervisor was in charge of two or three teams. Fieldwork began in October 2005 and concluded in January 2006. Interviewing took place everyday throughout the fieldwork period, although interviewing teams were permitted to take one day off per week.
Interviews averaged 35 minutes for the household questionnaire , 30 minutes for the women's questionnaire, and 25 for the under five children's questionnaire (excluding the anthropometry). Interviews were conducted primarily in Serbian, but they were translated into Albanian and Hungarian and these translated questionnaires were used when the respondent did not speak Serbian.
The overall field coordinators were: Natalija Biliskov, Dragana Djokovic Papic, Ljiljana Djordjevic and Tatjana Jovanov.
Data Collectors
| Name | Abbreviation |
|---|---|
| Statistical Office of the Republic of Serbia | SORS |
| Strategic Marketing Research Agency | SMMRI |
Questionnaires
Questionnaires
The questionnaires for the Serbia MICS were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes household characteristics, education, child labour, water and sanitation, security of tenure and durability od housing, child discipline, child disability and module used in Roma households living in Roma settlements.
In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child.
The women's questionnaire include women's characteristics, child mortality (this module was used only in Roma households living in Roma settlements), maternal and newborn health, security of tenure on eviction for the woman, marriage/union, contraception, attitudes toward domestic violence, sexual behaviour and HIV/AIDS.
The children's questionnaire includes children's characteristics, birth registration and early learning, child development, breastfeeding, care of illness, immunization, and anthropometry.
The questionnaires were developed in English from the MICS3 Model Questionnaires, and were translated into Serbian. After an initial review the questionnaires were translated back into English by an independent translator with no prior knowledge of the survey. The back translation from the Serbian version was independently reviewed and compared to the English original. Differences in translation were reviewed and resolved in collaboration with the original translators.
After adaptation, they were translated into Albanian and Hungarian, and were pre-tested in several places in Serbia.
All questionnaires and modules are provided as external resources.
In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child.
The women's questionnaire include women's characteristics, child mortality (this module was used only in Roma households living in Roma settlements), maternal and newborn health, security of tenure on eviction for the woman, marriage/union, contraception, attitudes toward domestic violence, sexual behaviour and HIV/AIDS.
The children's questionnaire includes children's characteristics, birth registration and early learning, child development, breastfeeding, care of illness, immunization, and anthropometry.
The questionnaires were developed in English from the MICS3 Model Questionnaires, and were translated into Serbian. After an initial review the questionnaires were translated back into English by an independent translator with no prior knowledge of the survey. The back translation from the Serbian version was independently reviewed and compared to the English original. Differences in translation were reviewed and resolved in collaboration with the original translators.
After adaptation, they were translated into Albanian and Hungarian, and were pre-tested in several places in Serbia.
All questionnaires and modules are provided as external resources.
Data Processing
Data Editing
Data editing took place at a number of stages throughout the processing (see Other processing), including:
a) Office editing and coding
b) During data entry
c) Structure checking and completeness
d) Secondary editing
e) Structural checking of SPSS data files
Detailed documentation of the editing of data can be found in the data processing guidelines.
a) Office editing and coding
b) During data entry
c) Structure checking and completeness
d) Secondary editing
e) Structural checking of SPSS data files
Detailed documentation of the editing of data can be found in the data processing guidelines.
Other Processing
Data were processed in clusters, with each cluster being processed as a complete unit through each stage of data processing. Each cluster goes through the following steps:
1) Questionnaire reception
2) Office editing and coding
3) Data entry
4) Structure and completeness checking
5) Verification entry
6) Comparison of verification data
7) Back up of raw data
8) Secondary editing
9) Edited data back up
After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:
10) Export to SPSS in 4 files (hh - household, hl - household members, wm - women, ch - children under 5)
11) Recoding of variables needed for analysis
12) Adding of sample weights
13) Calculation of wealth quintiles and merging into data
14) Structural checking of SPSS files
15) Data quality tabulations
16) Production of analysis tabulations
Details of each of these steps can be found in the data processing documentation, data editing guidelines, data processing programs in CSPro and SPSS, and tabulation guidelines.
Data entry was conducted by 20 data entry operators in tow shifts, supervised by 4 data entry supervisors, using a total of 24 computers (20 data entry computers plus 4 supervisors computers). Data entry was conducted at the Statistical Office of Serbia and SMMRI head office using manual data entry. For data entry, CSPro version 2.6.007 was used with a highly structured data entry program, using system controlled approach, that controlled entry of each variable. All range checks and skips were controlled by the program and operators could not override these. A limited set of consistency checks were also included inthe data entry program. In addition, the calculation of anthropometric Z-scores was also included in the data entry programs for use during analysis. Open-ended responses ("Other" answers) were not entered or coded.
Structure and completeness checking ensured that all questionnaires for the cluster had been entered, were structurally sound, and that women's and children's questionnaires existed for each eligible woman and child.
100% verification of all variables was performed using independent verification, i.e. double entry of data, with separate comparison of data followed by modification of one or both datasets to correct keying errors by original operators who first keyed the files.
After completion of all processing in CSPro, all individual cluster files were backed up before concatenating data together using the CSPro file concatenate utility.
For tabulation and analysis SPSS version 14.0 were used.
After transferring all files to SPSS, certain variables were recoded for use as background characteristics in the tabulation of the data, including grouping age, education, geographic areas as needed for analysis. In the process of recoding ages and dates some random imputation of dates (within calculated constraints) was performed to handle missing or "don't know" ages or dates. Additionally, a wealth (asset) index of household members was calculated using principal components analysis, based on household assets, and both the score and quintiles were included in the datasets for use in tabulations.
1) Questionnaire reception
2) Office editing and coding
3) Data entry
4) Structure and completeness checking
5) Verification entry
6) Comparison of verification data
7) Back up of raw data
8) Secondary editing
9) Edited data back up
After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:
10) Export to SPSS in 4 files (hh - household, hl - household members, wm - women, ch - children under 5)
11) Recoding of variables needed for analysis
12) Adding of sample weights
13) Calculation of wealth quintiles and merging into data
14) Structural checking of SPSS files
15) Data quality tabulations
16) Production of analysis tabulations
Details of each of these steps can be found in the data processing documentation, data editing guidelines, data processing programs in CSPro and SPSS, and tabulation guidelines.
Data entry was conducted by 20 data entry operators in tow shifts, supervised by 4 data entry supervisors, using a total of 24 computers (20 data entry computers plus 4 supervisors computers). Data entry was conducted at the Statistical Office of Serbia and SMMRI head office using manual data entry. For data entry, CSPro version 2.6.007 was used with a highly structured data entry program, using system controlled approach, that controlled entry of each variable. All range checks and skips were controlled by the program and operators could not override these. A limited set of consistency checks were also included inthe data entry program. In addition, the calculation of anthropometric Z-scores was also included in the data entry programs for use during analysis. Open-ended responses ("Other" answers) were not entered or coded.
Structure and completeness checking ensured that all questionnaires for the cluster had been entered, were structurally sound, and that women's and children's questionnaires existed for each eligible woman and child.
100% verification of all variables was performed using independent verification, i.e. double entry of data, with separate comparison of data followed by modification of one or both datasets to correct keying errors by original operators who first keyed the files.
After completion of all processing in CSPro, all individual cluster files were backed up before concatenating data together using the CSPro file concatenate utility.
For tabulation and analysis SPSS version 14.0 were used.
After transferring all files to SPSS, certain variables were recoded for use as background characteristics in the tabulation of the data, including grouping age, education, geographic areas as needed for analysis. In the process of recoding ages and dates some random imputation of dates (within calculated constraints) was performed to handle missing or "don't know" ages or dates. Additionally, a wealth (asset) index of household members was calculated using principal components analysis, based on household assets, and both the score and quintiles were included in the datasets for use in tabulations.
Data Appraisal
Estimates of Sampling Error
Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2005 MICS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors can be evaluated statistically. The sample of respondents to the Serbia 2005 MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which is the square root of the variance. Confidence intervals are calculated for each statistic within which the true value for the population can be assumed to fall. Plus or minus two standard errors of the statistic is used for key statistics presented in MICS, equivalent to a 95 percent confidence interval.
If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formula for calculating sampling errors. However, the Serbia 2005 MICS sample is the result of a multi-stage stratified design, and consequently needs to use more complex formulae. The SPSS complex samples module has been used to calculate sampling errors for the Serbia 2005 MICS. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. This method is documented in the SPSS file CSDescriptives.pdf found under the Help, Algorithms options in SPSS.
Sampling errors have been calculated for a select set of statistics (all of which are proportions due to the limitations of the Taylor linearization method) for the national sample, urban and rural areas, and for each of the six regions. For each statistic, the estimate, its standard error, the coefficient of variation (or relative error -- the ratio between the standard error and the estimate), the design effect, and the square root design effect (DEFT -- the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used), as well as the 95 percent confidence intervals (+/-2 standard errors).
Details of the sampling errors are presented in the sampling errors appendix to the report and in the sampling errors table presented in te external resources.
Sampling errors can be evaluated statistically. The sample of respondents to the Serbia 2005 MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which is the square root of the variance. Confidence intervals are calculated for each statistic within which the true value for the population can be assumed to fall. Plus or minus two standard errors of the statistic is used for key statistics presented in MICS, equivalent to a 95 percent confidence interval.
If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formula for calculating sampling errors. However, the Serbia 2005 MICS sample is the result of a multi-stage stratified design, and consequently needs to use more complex formulae. The SPSS complex samples module has been used to calculate sampling errors for the Serbia 2005 MICS. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. This method is documented in the SPSS file CSDescriptives.pdf found under the Help, Algorithms options in SPSS.
Sampling errors have been calculated for a select set of statistics (all of which are proportions due to the limitations of the Taylor linearization method) for the national sample, urban and rural areas, and for each of the six regions. For each statistic, the estimate, its standard error, the coefficient of variation (or relative error -- the ratio between the standard error and the estimate), the design effect, and the square root design effect (DEFT -- the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used), as well as the 95 percent confidence intervals (+/-2 standard errors).
Details of the sampling errors are presented in the sampling errors appendix to the report and in the sampling errors table presented in te external resources.
Data Appraisal
A series of data quality tables and graphs are available to review the quality of the data and include the following:
Age distribution of the household population
Age distribution of eligible women and interviewed women
Age distribution of eligible children and children for whom the mother or caretaker was interviewed
Age distribution of children under age 5 by 3 month groups
Age and period ratios at boundaries of eligibility
Percent of observations with missing information on selected variables
Presence of mother inthe household and person interviewed for the under 5 questionnaire
School attendance by single year age
Sex ratio at birth among children ever born, surviving and dead by age of respondent
Distribution of women by time since last birth
Scatterplot of weight by height, weight by age and height by age
Graph of male and female population by single years of age
Population pyramid
The results of each of these data quality tables is shown in the appendix of the final report and is also given in the external resources section.
The general rule for presentation of missing data in the final report tabulations is that a column is presented for missing data if the percentage of cases with missing data is 1% or more. Cases with missing data on the background characteristics (e.g. education) are included in the tables, but the missing data rows are suppressed and noted at the bottom of the tables in the report (not in the SPSS output, however).
Age distribution of the household population
Age distribution of eligible women and interviewed women
Age distribution of eligible children and children for whom the mother or caretaker was interviewed
Age distribution of children under age 5 by 3 month groups
Age and period ratios at boundaries of eligibility
Percent of observations with missing information on selected variables
Presence of mother inthe household and person interviewed for the under 5 questionnaire
School attendance by single year age
Sex ratio at birth among children ever born, surviving and dead by age of respondent
Distribution of women by time since last birth
Scatterplot of weight by height, weight by age and height by age
Graph of male and female population by single years of age
Population pyramid
The results of each of these data quality tables is shown in the appendix of the final report and is also given in the external resources section.
The general rule for presentation of missing data in the final report tabulations is that a column is presented for missing data if the percentage of cases with missing data is 1% or more. Cases with missing data on the background characteristics (e.g. education) are included in the tables, but the missing data rows are suppressed and noted at the bottom of the tables in the report (not in the SPSS output, however).
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Oliver Petrovic | UNICEF Belgrade | opetrovic@unicef.org | www.unicef.org/serbia |
| Dragisa Bjeloglav | SMMRI | dragisa.bjeloglav@smmri.com | www.smmri.com |
| Ivana Bjelic | SMMRI | ivana.bjelic@smmri.com | www.smmri.com |
| Dragana Djokovic - Papic | SORS | ddjokovic_papic@statserb.sr.gov.yu | www.statserb.sr.gov.yu |
| Jadranka Milanovic | UNICEF Belgrade | jmilanovic@unicef.org | www.unicef.org/serbia |
| George Sakvarelidze | UNICEF CEE/CIS Regional Office | gsakvarelidze@unicef.org | www.childinfo.org |
| Hancioglu, Attila | UNICEF Headquaters | ahancioglu@unicef.org | www.childinfo.org |
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, with the condition that we receive a the objectives of any research project that will be using the data prior to authorizing their distribution. Copies of all reports and publications based on the requested data must be sent to UNICEF Belgrade (belgrade@unicef.org).
Requests for access to the datasets may be made through the website: www.childinfo.org or email: belgrade@unicef.org.
Requests for access to the datasets may be made through the website: www.childinfo.org or email: belgrade@unicef.org.
Citation requirements
Statistical Office of the Republic of Serbia, Strategic Marketing Research Agency, Republic of Serbia. Republic of Serbia Multiple Indicator Cluster Survey: Household , household listing, women and children's files, 2005 [Computer file]. Belgrade, Republic of Serbia, UNICEF Belgrade [producer], 2007. Belgrade, Republic of Serbia: UNICEF Belgrade and New York: Strategic Information Section, Division of Policy and Planning, UNICEF [distributors], 2007.
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Oliver Petrovic | UNICEF Belgrade | belgrade@unicef.org | www.unicef.org/serbia |
| Jadranka Milanovic | UNICEF Belgrade | belgrade@unicef.org | www.unicef.org/serbia |
Disclaimer and copyrights
Disclaimer
UNICEF Belgrade provides these data to external users without any warranty or responsibility implied. UNICEF Belgrade accepts no responsibility for the results and/or implications of any actions resulting from the use of these data.
Copyright
2007, UNICEF Belgrade.
Metadata production
DDI Document ID
DDI_SRB_2005_MICS_v01_M
Producers
| Name | Affiliation | Role |
|---|---|---|
| Bjelic, Ivana | Strategic Marketing | Producer of Serbia MICS3 Archive |
| Zoric, Aleksandar | Strategic Marketing | Producer of Serbia MICS3 Archive |
| Petrovic, Oliver | United Nations Children Funds | Technical and financial support |
| Croft, Trevor | Blancroft Research International | Producer of generic example |
| James, Rhiannon | UNICEF | Adaption of Serbia MICS3 archive for childinfo.org |
Date of Metadata Production
2008-01-31
DDI Document version
Serbia MICS UNICEF 2005 v0.7
Slightly edited version of UNICEF's DDI ref. DDI-SRB-SORS-SMMRI-MICS-2005/0.6
Slightly edited version of UNICEF's DDI ref. DDI-SRB-SORS-SMMRI-MICS-2005/0.6