Multiple Indicator Cluster Survey 2005
Montenegro, 2005 - 2006
Get Microdata
Reference ID
MNE_2005_MICS_v01_M
Producer(s)
Statistical Office of the Republic of Montenegro, SMMRI, UNICEF Podgorica, MICS3 Global Team
Collection(s)
Created on
Mar 21, 2011
Last modified
Sep 26, 2013
Page views
200696
Downloads
7531
Identification
Survey ID Number
MNE_2005_MICS_v01_M
Title
Multiple Indicator Cluster Survey 2005
Country/Economy
| Name | Country code |
|---|---|
| Montenegro | MNE |
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 Montenegro Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Montenegro.
- 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 Montenegro 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 Montenegro (MONSTAT) and the Strategic Marketing Research Agency (SMMRI), with the support and assistance of UNICEF and other partners. Technical assistance and training for the survey was 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 Montenegro: 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; Preparation of report.
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.
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 Montenegro Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Montenegro.
- 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 Montenegro 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 Montenegro (MONSTAT) and the Strategic Marketing Research Agency (SMMRI), with the support and assistance of UNICEF and other partners. Technical assistance and training for the survey was 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 Montenegro: 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; Preparation of report.
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.
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
2007-12-09
Scope
Notes
The scope of the Multiple Indicator Cluster Survey includes:
HOUSEHOLD: Household listing, Education, Water and Sanitation, Household characteristics, Child labour, Child Discipline, and Child Disability.
WOMEN: Women's characteristics, 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, and Child Disability.
WOMEN: Women's characteristics, 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 |
| Women's background | 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 survey is nationally representative and covers the whole of Montenegro.
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 |
|---|---|
| Statistical Office of the Republic of Montenegro | MONSTAT |
| SMMRI | Strategic Marketing |
| UNICEF Podgorica | United Nations Childrens Funds Podgorica |
| MICS3 Global Team | United Nations Childrens Funds NYHQ |
Producers
| Name | Affiliation | Role |
|---|---|---|
| UNICEF Podgorica | United Nations Childrens Founds Podgorica | 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 |
|---|---|---|
| Bjelic, Ivana | SMMRI | Technical implementation in all phases |
| Bjeloglav, Dragisa | SMMRI | National coordinator |
| Croft, Trevor | UNICEF | Conceptualization and design of MICS survey |
| Diakhate, Ngagne | UNICEF | On-line technical support on data processing and analysis |
| Djurkovic, Boro | MONSTAT | MICS DevInfo data base administrator |
| Hancioglu, Attila | UNICEF | Conceptualization and design of MICS survey, overall cordination |
| Holmberg, Emma | UNICEF | On-line technical support on data processing and analysis |
| Kovacevic, Branka | UNICEF Podgorica | Supervision and coordination of MICS survey |
| Loaiza, Eldiberto | UNICEF | Conceptualization and design of MICS survey |
| Petrovic, Oliver | UNICEF Belgrade | Overall coordination |
| Raicevic, Vlado | SMMRI | SMMRI field supervisor |
| Remikovic, Snezana | MONSTAT | MONSTAT team leader |
| Sakvarelidze, George | UNICEF | Regional coordination |
| Segone, Marco | UNICEF | Conceptualization and design of MICS survey |
| Svensson, Ann-Lis | UNICEF | Inclusion of the most exluded population group in the survey design |
| Wardlaw, Tessa | 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 3 regions (South, Central and North) for key indicators.
Each region in Montenegro is subdivided into municipalities. Each municipality is divided into settlements and each settlement into enumeration areas. In total Montenegro includes 21 municipalities, 1256 settlements and 3201 enumeration areas. The sample frame for this survey was based on the list of enumeration areas developed from the 2003 population census.
The primary sampling unit (PSU), the cluster for the 2005 MICS, is defined on the basis of the enumeration areas from the census frame. 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 2003 Population Census
A stratified, two-stage random sampling approach was used for the selection of the survey sample.
Regions were identified as the main sampling domains and the sample was selected in two stages. Within each region, 141 census enumeration areas were selected with probability proportional to size. Based on updated data from the last census (2003), those units were divided into clusters of 18 households on average. Important factor, which influenced on sample design, is very low fertility rate and small number of household members. For example, one generation of born children makes less than 2 percent of population, and average number of household members is 3.4. Due to these facts, we stratified the households in selected enumeration areas to two strata. One stratum contained households with children, and the other one contained households without children. Allocation of sample in the stratum of households with children was significantly bigger than allocation of sample in the stratum of households without children.
After a household listing was carried out within the selected enumeration areas, a systematic sample of 2,575 households was drawn. The sample was stratified by region and two more strata: households with children and household without children, and is not self-weighting. For reporting national level results, sample weights are used.
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 Montenegro 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 3 regions (South, Central and North) for key indicators.
Each region in Montenegro is subdivided into municipalities. Each municipality is divided into settlements and each settlement into enumeration areas. In total Montenegro includes 21 municipalities, 1256 settlements and 3201 enumeration areas. The sample frame for this survey was based on the list of enumeration areas developed from the 2003 population census.
The primary sampling unit (PSU), the cluster for the 2005 MICS, is defined on the basis of the enumeration areas from the census frame. 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 2003 Population Census
A stratified, two-stage random sampling approach was used for the selection of the survey sample.
Regions were identified as the main sampling domains and the sample was selected in two stages. Within each region, 141 census enumeration areas were selected with probability proportional to size. Based on updated data from the last census (2003), those units were divided into clusters of 18 households on average. Important factor, which influenced on sample design, is very low fertility rate and small number of household members. For example, one generation of born children makes less than 2 percent of population, and average number of household members is 3.4. Due to these facts, we stratified the households in selected enumeration areas to two strata. One stratum contained households with children, and the other one contained households without children. Allocation of sample in the stratum of households with children was significantly bigger than allocation of sample in the stratum of households without children.
After a household listing was carried out within the selected enumeration areas, a systematic sample of 2,575 households was drawn. The sample was stratified by region and two more strata: households with children and household without children, and is not self-weighting. For reporting national level results, sample weights are used.
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 Montenegro 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 2,575 households selected for the sample, 2,494 were found to be occupied. Of these, 2,358 were successfully interviewed for a household response rate of 95 percent. The household response rate was higher in the North (97 percent) than in the Central and in the South (93 percent). In the interviewed households, 2,385 women (age 15-49) were identified. Of these, 2,258 were successfully interviewed, yielding a response rate of 95 percent. The women response rate was higher in the Central and North region (95 percent) than in the in the South (93 percent). In addition, 1,072 children under age five were listed in the household questionnaire. Questionnaires were completed for 1.061 of these children, which corresponds to a response rate of 99 percent. This response rates are very similar across the regions. Overall response rates of 90 and 94 are calculated for the women's and under-5's interviews, respectively.
Weighting
Sample weights were calculated for each of the datasets.
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.
The household weight variable is called HHWEIGHT and is used with the household data. Same weight is applied to the household listing data. 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.
The household weight variable is called HHWEIGHT and is used with the household data. Same weight is applied to the household listing data. 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 |
|---|---|
| 2005-10-05 | 2006-01-11 |
Data Collection Mode
Face-to-face [f2f]
Supervision
The data were collected by 6 teams; each was comprised of three or four interviewers, one driver, one editor/measurer and a supervisor. 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 Podgorica 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 Podgorica also made 3 visits to field teams to provide support and to review progress.
Data Collection Notes
The Statistical Office of the Republic of Montenegro (MONSTAT) and The Strategic Marketing Research Agency were responsible for data collection. The whole territory of Montenegro was divided into 5 districts according to the regional network of institutions responsible for listing and fieldwork. In each district one or two teams 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 Podgorica.
The data were collected by 6 teams; each was comprised of three or four interviewers, one driver, one editor/measurer and a supervisor. 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 Montenegrian, but they were translated into Albanian and these translated questionnaires were used when the respondent did not speak Montenegrian.
The overall field coordinators were: Itana Labovic, Snezana Remikovic and Vladimir Raicevic.
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 Podgorica.
The data were collected by 6 teams; each was comprised of three or four interviewers, one driver, one editor/measurer and a supervisor. 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 Montenegrian, but they were translated into Albanian and these translated questionnaires were used when the respondent did not speak Montenegrian.
The overall field coordinators were: Itana Labovic, Snezana Remikovic and Vladimir Raicevic.
Data Collectors
| Name | Abbreviation |
|---|---|
| Statistical Office of the Republic of Montenegro | MONSTAT |
| Strategic Marketing Research Agency | SMMRI |
Questionnaires
Questionnaires
The questionnaires for the Montenegro 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, and child disability.
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, 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 Montenegrian. 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 Montenegrian 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 were pre-tested in several places in Podgorica.
All questionnaires and modules can be found in the questionnaire sub-folder.
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, 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 Montenegrian. 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 Montenegrian 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 were pre-tested in several places in Podgorica.
All questionnaires and modules can be found in the questionnaire sub-folder.
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.
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.
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.
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.
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 | |
|---|---|---|---|
| Remikovic, Snezana | MONSTAT | snezanarem@mn.yu | www.monstat.cg.yu |
| Bjeloglav, Dragisa | SMMRI | dragisa.bjeloglav@smmri.com | www.smmri.com |
| Bjelic, Ivana | SMMRI | ivana.bjelic@smmri.com | www.smmri.com |
| Sakvarelidze, George | UNICEF | gsakvarelidze@unicef.org | www.childinfo.org |
| Kovacevic, Branka | UNICEF Podgorica | bkovacevic@unicef.org | www.unicef.org/montenegro |
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 an abstract or a detailed description 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 Podgorica:
bkovacevic@unicef.org
podgorica@unicef.org
Requests for access to the datasets may be made through the website: www.childinfo.org or email: podgorica@unicef.org.
bkovacevic@unicef.org
podgorica@unicef.org
Requests for access to the datasets may be made through the website: www.childinfo.org or email: podgorica@unicef.org.
Citation requirements
Statistical Office of the Republic of Montenegro, Strategic Marketing Research Agency, Republic of Montenegro. Montenegro Multiple Indicator Cluster Survey: Household , household listing, women and children's files, 2005 [Computer file]. Podgorica, Republic of Montenegro, UNICEF Podgorica [producer], 2007. Podgorica, Republic of Montenegro: UNICEF Podgorica and New York: Strategic Information Section, Division of Policy and Planning, UNICEF [distributors], 2007.
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Kovacevic, Branka | UNICEF Podgorica | podgorica@unicef.org | www.unicef.org/montenegro |
Disclaimer and copyrights
Disclaimer
UNICEF Podgorica provides these data to external users without any warranty or responsibility implied. UNICEF Podgorica accepts no responsibility for the results and/or implications of any actions resulting from the use of these data.
Copyright
2007, UNICEF Podgorica.
Metadata production
DDI Document ID
DDI_MNE_2005_MICS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Bjelic, Ivana | SMMRI | Strategic Marketing | Data producer and customization of generic template |
| Croft, Trevor | TNC | Blancroft Research International | Producer of generic example |
| Djurkovic, Boro | MONSTAT | The Statistical Office of the Republic of Montenegro | Data producer and customization of generic template |
| Kovacevic, Branka | UNICEF | United Nations Children Funds | Technical support |
| Remikovic, Snezana | MONSTAT | The Statistical Office of the Republic of Montenegro | Data producer and customization of generic template |
| James, Rhiannon | UNICEF | Adaption of Montenegro MICS archive for www.childinfo.org |
Date of Metadata Production
2008-02-13
DDI Document version
Montenegro UNICEF MICS 2005 v0.1
Slightly edited version of UNICEF's DDI ref. DDI-SRB-UNICEF-SMMRI-MICS-2005/1.0
Slightly edited version of UNICEF's DDI ref. DDI-SRB-UNICEF-SMMRI-MICS-2005/1.0