Multiple Indicator Cluster Survey 2006
Kyrgyz Republic, 2005
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Reference ID
KGZ_2005_MICS_v01_M
Producer(s)
National Statistical Committee of the Kyrgyz Republic
Collection(s)
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Mar 21, 2011
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Identification
Survey ID Number
KGZ_2005_MICS_v01_M
Title
Multiple Indicator Cluster Survey 2006
Translated Title
Multiple Indicator Cluster Survey (MICS) Kyrgyz Republic, 2006
Country/Economy
| Name | Country code |
|---|---|
| Kyrgyz Republic | KGZ |
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 around 1995 (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 2006 Kyrgyz Republic Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Kyrgyz Republic
- 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 Kyrgyz Republic 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 National Statistical Committee of the Kyrgyz Republic, 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.
Survey Objectives
The 2006 Kyrgyz Republic Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Kyrgyz Republic
- 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 Kyrgyz Republic 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 National Statistical Committee of the Kyrgyz Republic, 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.
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
2006-11-01
Scope
Notes
The multiple Indicator Cluster Survey in Kyrgyz Republic included the following modules in the questionnaires: HOUSEHOLD QUESTIONNAIRE :
Household listing, Education, Water and sanitation, Household characteristics, Child labour, Child discipline, Maternal mortality and Consumption of iodized salt.
WOMEN'S QUESTIONNAIRE: Women's characteristics, Child mortality, Tetanus toxoid, Maternal and newborn health, Marriage/union, Contraception, Attitude toward domestic violence, Sexual behavior and HIV/AIDS knowledge.
CHILDREN'S QUESTIONNAIRE: Children's characteristics, Birth registration and early learning, Child development, Vitamin A, Immunization, Breastfeeding, Treatment of illness and care and Anthropometric data
Household listing, Education, Water and sanitation, Household characteristics, Child labour, Child discipline, Maternal mortality and Consumption of iodized salt.
WOMEN'S QUESTIONNAIRE: Women's characteristics, Child mortality, Tetanus toxoid, Maternal and newborn health, Marriage/union, Contraception, Attitude toward domestic violence, Sexual behavior and HIV/AIDS knowledge.
CHILDREN'S QUESTIONNAIRE: Children's characteristics, Birth registration and early learning, Child development, Vitamin A, Immunization, Breastfeeding, Treatment of illness and care and Anthropometric data
Topics
| Topic | Vocabulary |
|---|---|
| Household members | MICS Topics |
| Education | MICS Topics |
| Water and sanitation | MICS Topics |
| Household characteristics | MICS Topics |
| Child labour | MICS Topics |
| Salt iodization | MICS Topics |
| Women's background | MICS Topics |
| Child mortality | MICS Topics |
| Tetanus toxoid | MICS Topics |
| Maternal and newborn health | MICS Topics |
| Marriage and union | MICS Topics |
| Contraception | MICS Topics |
| HIV/AIDS | MICS Topics |
| Children's background | MICS Topics |
| Birth registration | MICS Topics |
| Early learning | MICS Topics |
| Vitamin A | MICS Topics |
| Breastfeeding | MICS Topics |
| Care of illness | MICS Topics |
| Immunization | MICS Topics |
| Anthropometry | MICS Topics |
| Sexual behaviour | MICS Topics |
| Durability of housing | MICS Topics |
| Child discipline | MICS Topics |
| Attitudes towards domestic violence | MICS Topics |
| Child development | MICS Topics |
| Maternal mortality | MICS Topics |
Coverage
Geographic Coverage
The survey is nationally representative and covers the whole of Kyrgyz Republic.
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 |
|---|
| National Statistical Committee of the Kyrgyz Republic |
Producers
| Name | Affiliation | Role |
|---|---|---|
| National Statistical Committee of the Kyrgyz Republic | Technical implementation and supervision | |
| UNICEF, Kyrgyz Republic Country Office | UNICEF | Technical assistance |
| UNICEF Regional MICS coordinator | UNICEF | International technical assistance |
| UNICEF Regional M&E officer | UNICEF | International technical assistance |
| Strategic Information Section, Division of Policy and Planning, UNICEF NYHQ | UNICEF | International technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| UNICEF | UNICEF | Funding of survey implementation |
Sampling
Sampling Procedure
The sample for the Kyrgyzstan Multiple Indicator Cluster Survey was designed to provide representative estimates of MICS indicators at the national level, in urban and rural areas, as well as for eight regions: Batken, Jalalabad, Issyk Kul, Naryn, Osh, Talas, Chui regions, and Bishkek. The urban and rural areas of each region were used as strata, where the sample design was made in two stages.
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 2006 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.
Four hundred clusters, or Census-1999 Enumeration Areas (CEA), were selected with a probability proportional to the population size in the first stage. For rural areas, populated settlements were used as Primary Sampling Units (PSUs). For urban areas, internal territorial-administrative units were used as PSUs. For each enumeration area, a household listing was updated and used as a sample framework for the second selection stage. Later, households with an equal probability were selected, according to the up-dated lists of addresses.
In defining the cluster size, a high rate of intra-cluster correlation of different indicators was taken into account. This required clusters of small size, as well as consideration of the effective use of interviewers' time, requiring a minimization of movement from one settlement to another. As a compromise between data accuracy and the efficient use of limited time and funding, a cluster size was determined to consist of 13 households.
Thus, a total sample volume consisted of 5,200 households. Given that a sample is not self-weighting, and that sample size by strata is approximately equal, sample weights were used for reporting national level results.
The sampling procedures are more fully described in the sampling design document and the sampling appendix of the final report.
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 2006 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.
Four hundred clusters, or Census-1999 Enumeration Areas (CEA), were selected with a probability proportional to the population size in the first stage. For rural areas, populated settlements were used as Primary Sampling Units (PSUs). For urban areas, internal territorial-administrative units were used as PSUs. For each enumeration area, a household listing was updated and used as a sample framework for the second selection stage. Later, households with an equal probability were selected, according to the up-dated lists of addresses.
In defining the cluster size, a high rate of intra-cluster correlation of different indicators was taken into account. This required clusters of small size, as well as consideration of the effective use of interviewers' time, requiring a minimization of movement from one settlement to another. As a compromise between data accuracy and the efficient use of limited time and funding, a cluster size was determined to consist of 13 households.
Thus, a total sample volume consisted of 5,200 households. Given that a sample is not self-weighting, and that sample size by strata is approximately equal, sample weights were used for reporting national level results.
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
During the course of the survey, all 400 PSUs selected at the first sampling stage were visited. A list of household addresses was made for those PSUs. Out of 5,200 sample households, 5,199 were found to be occupied (Table ??.1). Out of these populated households, 5,179 were successfully interviewed, yielding a household response rate of 99.6%. In all regions except for Naryn, the interviewers managed to carry out interviews in all selected households.
In the interviewed households 7,043 women (aged 15-49) were identified. Of these women, 6,973 were successfully interviewed, which corresponds to a response rate of 99.0%. Additionally, the household sample accounted for 3,000children under five years of age, and 2,987 questionnaires were completed on these, for a response rate of 99.6.
In the interviewed households 7,043 women (aged 15-49) were identified. Of these women, 6,973 were successfully interviewed, which corresponds to a response rate of 99.0%. Additionally, the household sample accounted for 3,000children under five years of age, and 2,987 questionnaires were completed on these, for a response rate of 99.6.
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. The household weight variable is called HHWEIGHT and is used with the HH data and the HL data.
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.
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. The household weight variable is called HHWEIGHT and is used with the HH data and the HL data.
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.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2005-11-30 | 2005-12-30 | northern regions |
Data Collection Mode
Face-to-face [f2f]
Supervision
Interviewing was conducted by teams of interviewers. Each interviewing team comprised of 3 interviewers, a field editor and a driver. Each teams used a vehicle to travel from cluster to cluster (and where necessary within cluster).
The role of the supervisor was to coordinator 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 was responsible for describing survey objectives to household head, and get permission for interviewing, he/she 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 NSC also made 3 visits to field teams to provide support and to review progress.
The role of the supervisor was to coordinator 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 was responsible for describing survey objectives to household head, and get permission for interviewing, he/she 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 NSC also made 3 visits to field teams to provide support and to review progress.
Data Collection Notes
The interviewers have been adequately trained to collect data and apply questions. Training included lectures on interviewing techniques and the contents of the questionnaires, and mock interviews between trainees to gain practice in asking questions. Training was conducted in two rounds: for northern regions from November 23-27, 2005; for southern regions from December 8-11, 2005. The data were collected by 25 teams, each comprised of three interviewers, one driver and one editor. The editor was responsible for ensuring data quality and use of proper interview techniques, establishing initial contact with households and remaining in constant connection with a regional supervisor.
The fieldwork started in the northern regions on November 30, 2005, and was completed on December 30, 2005. The data collection in the southern regions was conducted from December 18, 2005 to February 3, 2006.
Each interviewing team comprised of 3 interviewers, together with a field editor and a driver. A total of 75 interviewers, 8 supervisors and 25 field editors were used. Data collection took place over a period of about 6 weeks. Interviewing took place everyday throughout the fieldwork period, although interviewing teams were permitted to take one day off per week. Interviews were conducted primarily in Kyrgyz and Russian. On average interviewing in one household took around 50 minutes.
Seven staff members of NSC provided overall fieldwork coordination and supervision. The overall field coordinator was Galina Samohleb.
The fieldwork started in the northern regions on November 30, 2005, and was completed on December 30, 2005. The data collection in the southern regions was conducted from December 18, 2005 to February 3, 2006.
Each interviewing team comprised of 3 interviewers, together with a field editor and a driver. A total of 75 interviewers, 8 supervisors and 25 field editors were used. Data collection took place over a period of about 6 weeks. Interviewing took place everyday throughout the fieldwork period, although interviewing teams were permitted to take one day off per week. Interviews were conducted primarily in Kyrgyz and Russian. On average interviewing in one household took around 50 minutes.
Seven staff members of NSC provided overall fieldwork coordination and supervision. The overall field coordinator was Galina Samohleb.
Data Collectors
| Name | Abbreviation |
|---|---|
| National Statistical Committee of the Kyrgyz Republic | NSC |
Questionnaires
Questionnaires
The questionnaires for the Kyrgyzstan 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, relationship, and orphanhood status. The household questionnaire includes household characteristics, Household listing, Education, Water and sanitation, Household characteristics, Child labour, Child discipline, Maternal mortality, consumption of iodized salt and durability of housing.
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, maternal and newborn health, marriage/union, contraception, attitude toward domestic violence, sexual behavior ans HIV/AIDS knowledge.
The children's questionnaire includes children's characteristics, birth registration and early learning, child development, vitamin A, breastfeeding, immunization, treatment of illness and care and anthropometric data.
The questionnaires are based on the MICS3 model questionnaire. The English version of questionnaires was translated into Kyrgyz and Russian languages and was pre-tested in August 2005. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.
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, maternal and newborn health, marriage/union, contraception, attitude toward domestic violence, sexual behavior ans HIV/AIDS knowledge.
The children's questionnaire includes children's characteristics, birth registration and early learning, child development, vitamin A, breastfeeding, immunization, treatment of illness and care and anthropometric data.
The questionnaires are based on the MICS3 model questionnaire. The English version of questionnaires was translated into Kyrgyz and Russian languages and was pre-tested in August 2005. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.
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.
The data processing was centralized. The field editors checked, cleared and packed the questionnaires by clusters, then questionnaires were delivered to the central office of the National Statistical Committee for further processing. Each incoming pack was registered and simultaneously the database was created.
Data were entered on twenty computers using CSPro software version 2.6.007. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS3 project and adapted to the Kyrgyz questionnaire were used throughout. Data processing began simultaneously with data collection in December 2005, and was finished in spring of 2006. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program, version 14, and the model syntax and tabulation plans developed by UNICEF for this purpose.
All data entry was conducted at the NSC 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, except in rare circumstances where the response matched an existing code in the questionnaire.
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 versions 10.0 and 14.0 were used. Version 10.0 was originally used for all tabulation programs, except for child mortality. Later version 14.0 was used for child mortality, data quality tabulations and other analysis activities.
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.
The data processing was centralized. The field editors checked, cleared and packed the questionnaires by clusters, then questionnaires were delivered to the central office of the National Statistical Committee for further processing. Each incoming pack was registered and simultaneously the database was created.
Data were entered on twenty computers using CSPro software version 2.6.007. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS3 project and adapted to the Kyrgyz questionnaire were used throughout. Data processing began simultaneously with data collection in December 2005, and was finished in spring of 2006. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program, version 14, and the model syntax and tabulation plans developed by UNICEF for this purpose.
All data entry was conducted at the NSC 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, except in rare circumstances where the response matched an existing code in the questionnaire.
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 versions 10.0 and 14.0 were used. Version 10.0 was originally used for all tabulation programs, except for child mortality. Later version 14.0 was used for child mortality, data quality tabulations and other analysis activities.
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 2006 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 2006 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 formulae for calculating sampling errors. However, the 2006 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 2006 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 five 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 2006 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 formulae for calculating sampling errors. However, the 2006 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 2006 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 five 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 | |
|---|---|---|---|
| Samohleb, Galina | National Statistical Committee of the Kyrgyz Republic | gsamohleb@stat.kg | www.stat.kg |
| Minbaev, Muktar | UNICEF/CO | mminbaev@unicef.org | www.childinfo.org |
| Hancioglu, Attila | UNICEF | 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 description of the research objectives prior to authorizing their distribution. Copies of all reports and publications based on the requested data must be sent to NSC (www.stat.kg) and UNICEF:
MICS3 Focal Point - Dr. Muktar Minbaev
Research, Monitoring & Evaluation PO,
UNICEF, Kyrgyz Republic
UN HOUSE, Chui Ave., 160, Bishkek,
Tel. +996 312 611211 ext. 220
Fax. +996 312 611191
Email: mminbaev@unicef.org
Requests for access to the datasets may be made through the website www.childinfo.org.
MICS3 Focal Point - Dr. Muktar Minbaev
Research, Monitoring & Evaluation PO,
UNICEF, Kyrgyz Republic
UN HOUSE, Chui Ave., 160, Bishkek,
Tel. +996 312 611211 ext. 220
Fax. +996 312 611191
Email: mminbaev@unicef.org
Requests for access to the datasets may be made through the website www.childinfo.org.
Citation requirements
National Statistical Committee of the Kyrgyz Republic, Kyrgyz Republic. Multiple Indicator Cluster Survey: Household , household listing, women and children's files, 2006 [Computer file]. Bishkek, Kyrgyz Republic: National Statistical Committee of the Kyrgyz Republic [producer], 2006. Bishkek, Kyrgyz Republic: National Statistical Committee of the Kyrgyz Republic and New York: Strategic Information Section, Dvision of Policy and Planning, UNICEF [distributors], 2006.
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Galina Samohleb, Ms. | National Statistical Committee of the Kyrgyz Republic | gsamohleb@stat.kg | www.stat.kg |
Disclaimer and copyrights
Disclaimer
NSC provides these data to external users without any warranty or responsibility implied. NSC accepts no responsibility for the results and/or implications of any actions resulting from the use of these data.
Metadata production
DDI Document ID
DDI_KGZ_2005_MICS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Praslova, Larisa | LP | National Statistical Committee of the Kyrgyz Republic | Data producer and customization of generic template |
| Croft, Trevor | TNC | Blancroft Research International | Producer of generic example |
| Zoric, Aleksandar | AZ | Strategic Marketing | Customization of generic template |
| James, Rhiannon | UNICEF | Adaption of archive for childinfo.org |
Date of Metadata Production
2008-02-26
DDI Document version
Kyrgyz Republic MICS 2006 v0.2
Slightly edited version of UNICEF's DDI ref. DDI-KGZ-CSO-MICS2006/1.0-v0.2
Slightly edited version of UNICEF's DDI ref. DDI-KGZ-CSO-MICS2006/1.0-v0.2