Multiple Indicator Cluster Survey 2006
Kazakhstan, 2006
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Reference ID
KAZ_2006_MICS_v01_M
Producer(s)
The Agency of Statistics of the Republic of Kazakhstan
Collection(s)
Created on
Mar 22, 2011
Last modified
Sep 26, 2013
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Identification
Survey ID Number
KAZ_2006_MICS_v01_M
Title
Multiple Indicator Cluster Survey 2006
Country/Economy
| Name | Country code |
|---|---|
| Kazakhstan | KZK |
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 Kazakhstan Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Kazakhstan
- 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 Kazakhstan 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 Agency of Statistics of the Republic of Kazakhstan, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.
Survey Objectives
The 2006 Kazakhstan Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Kazakhstan
- 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 Kazakhstan 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 Agency of Statistics of the Republic of Kazakhstan, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.
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
2006-08-06
Scope
Notes
The Kazakhstan Multiple Indicator Cluster Survey included the following modules in the questionnaires:
HOUSEHOLD QUESTIONNAIRE : Household characteristics, household listing, education, child labour, water and sanitation, household use of salt iodization, with optional modules for child discipline, maternal mortality and Kazakhstan specific modules UNICEF, Healthcare System Information, Primary Healthcare Accessibility and Accessibility Of In-Patient and Specialized Health Care.
WOMEN'S QUESTIONNAIRE: Women's characteristics, child mortality, maternal and newborn health, marriage and union, contraception, and HIV/AIDS knowledge, with optional modules for domestic violence, and sexual (reproductive) behavior and Kazakhstan specific module for Tuberculosis.
CHILDREN'S QUESTIONNAIRE: Children's characteristics, birth registration and early learning, breastfeeding, care of illness, immunization, and anthropometry, with an optional module for child development.
HOUSEHOLD QUESTIONNAIRE : Household characteristics, household listing, education, child labour, water and sanitation, household use of salt iodization, with optional modules for child discipline, maternal mortality and Kazakhstan specific modules UNICEF, Healthcare System Information, Primary Healthcare Accessibility and Accessibility Of In-Patient and Specialized Health Care.
WOMEN'S QUESTIONNAIRE: Women's characteristics, child mortality, maternal and newborn health, marriage and union, contraception, and HIV/AIDS knowledge, with optional modules for domestic violence, and sexual (reproductive) behavior and Kazakhstan specific module for Tuberculosis.
CHILDREN'S QUESTIONNAIRE: Children's characteristics, birth registration and early learning, breastfeeding, care of illness, immunization, and anthropometry, with an optional module for child development.
Topics
| Topic | Vocabulary |
|---|---|
| Household members | MICS Topics |
| Education | MICS Topics |
| Water and sanitation | MICS Topics |
| Household characteristics | MICS Topics |
| Child labour | MICS Topics |
| Child discipline | MICS Topics |
| Maternal mortality | MICS Topics |
| Salt iodization | MICS Topics |
| Child mortality | MICS Topics |
| Maternal and newborn health | MICS Topics |
| Marriage and union | MICS Topics |
| Contraception | MICS Topics |
| Attitudes towards domestic violence | MICS Topics |
| HIV/AIDS | MICS Topics |
| Reproductive Behavior | MICS Topics |
| Tuberculosis | MICS Topics |
| Birth registration and Early learning | MICS Topics |
| Child development | MICS Topics |
| Breastfeeding | MICS Topics |
| Care of illness | MICS Topics |
| Immunization | MICS Topics |
| Anthropometry | MICS Topics |
| Women's background | MICS Topics |
| Children's background | MICS Topics |
Coverage
Geographic Coverage
The sample for the Kazakhstan Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for urban and rural areas, as well as at sub-national level for 16 regions - 14 Oblasts and 2 Cities:
- Akmola Oblast
- Aktobe Oblast
- Almaty Oblast
- Atyrau Oblast
- West Kazakhstan Oblast
- Zhambyl Oblast
- Karaganda Oblast
- Kostanai Oblast
- Kyzylorda Oblast
- Mangistau Oblast
- South Kazakhstan Oblast
- Pavlodar Oblast
- North Kazakhstan Oblast
- East Kazakhstan Oblast
- Astana City
- Almaty City
- Akmola Oblast
- Aktobe Oblast
- Almaty Oblast
- Atyrau Oblast
- West Kazakhstan Oblast
- Zhambyl Oblast
- Karaganda Oblast
- Kostanai Oblast
- Kyzylorda Oblast
- Mangistau Oblast
- South Kazakhstan Oblast
- Pavlodar Oblast
- North Kazakhstan Oblast
- East Kazakhstan Oblast
- Astana City
- Almaty City
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 |
|---|
| The Agency of Statistics of the Republic of Kazakhstan |
Producers
| Name | Affiliation | Role |
|---|---|---|
| The Agency of Statistics of the Republic of Kazakhstan | Technical implementation and supervision | |
| UNICEF, Kazakhstan 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 |
| Agency for International Development | USAID | Funding of survey implementation |
| UN Population Fund | UNFPA | Funding of survey implementation |
| UN Resident Coordinator Fund | UN ResCor | Funding of survey implementation |
| International Labor Organization | ILO | Funding of survey implementation |
| Organisation for economic co-operation and development | OECD | Financial and technical support in data archiving |
Sampling
Sampling Procedure
Regions were identified as the main sampling domains and the sample was selected in two stages. The sample was stratified by urban and rural areas (which represent second level territorial and administrative units). 1999 Population Census enumeration areas were selected as Primary Sampling Units (PSUs). The number of primary sampling units (PSUs) for oblast and main cities depended on the total population at the beginning of 2005.
At the first stage, mentioned number of PSUs was randomly selected for each stratum. In general, 625 PSUs were selected within the country. At the second stage, 24 households were systematically selected in each sampled primary sampling unit. Thus, total number of sampled households made 15,000.
The sample was stratified by region and is not self-weighting. For reporting national level results, sample weights are used.
For more information on the sampling design please see the sampling design document under the technical documents folder.
At the first stage, mentioned number of PSUs was randomly selected for each stratum. In general, 625 PSUs were selected within the country. At the second stage, 24 households were systematically selected in each sampled primary sampling unit. Thus, total number of sampled households made 15,000.
The sample was stratified by region and is not self-weighting. For reporting national level results, sample weights are used.
For more information on the sampling design please see the sampling design document under the technical documents folder.
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 15,000 households selected for the sample, 14,984 were found to be occupied. Of these 14,564 were successfully interviewed for a household response rate of 97.2 percent. In the interviewed households, 14,719 women (age 15-49) were identified. Of these, 14,570 were successfully interviewed, yielding a response rate of 99.0 percent. In addition, 4,424 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 4,416, which correspond to a response rate of 99.8 percent. Overall response rates calculated for the interviews of women 15-49 years of age and children under-5 were 96.2 and 97.0 percents respectively.
Household response rates in rural areas were higher than in urban - 99.4 and 95.6 percent respectively. Overall household response rate throughout the country was high and varied from 91.6 percent in Almaty City up to 99 percent in Zhambyl Oblast.
Household response rates in rural areas were higher than in urban - 99.4 and 95.6 percent respectively. Overall household response rate throughout the country was high and varied from 91.6 percent in Almaty City up to 99 percent in Zhambyl Oblast.
Weighting
Sample weights were calculated for each of the datafiles.
Kazakhstan Multiple Indicator Cluster Survey sample is not self-weighted. Essentially, by allocating equal numbers of households to each of the regions, different sampling fractions were used in each region since the size of the regions varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data.
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.
Kazakhstan Multiple Indicator Cluster Survey sample is not self-weighted. Essentially, by allocating equal numbers of households to each of the regions, different sampling fractions were used in each region since the size of the regions varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data.
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 |
|---|---|
| 2006-01 | 2006-03 |
Data Collection Mode
Face-to-face [f2f]
Supervision
Interviewing was conducted by teams of interviewers. Each interviewing team comprised of 3-4 female interviewers, a field editor and a supervisor, and a driver. 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 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 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 ASRK 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 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 ASRK also made 3 visits to field teams to provide support and to review progress.
Data Collection Notes
Personal list of team members for 16 domains was composed out of Oblast/City Statistics Departments staff. Training on data collection techniques in the fields was conducted in November-December 2005. Four regional training workshops by 6 days each were conducted in Petropavlovsk City (21-26 November), Shymkent City (28 November - 3 December), Semipalatinsk City (5 - 10 December) and Aktobe City (20 - 25 December) for the staff of regional departments involved in fieldwork. In total, 129 Statistic Division's staff members were trained.
Four teams by eight people from each Oblast participated in each workshop, in total 32 people. Training included lectures on interviewing techniques, contents of the questionnaires and mock interviews between trainees in practice interviewing. By the end of the training participants spent two days in practicing interviewing at the venue of training workshops. With the purpose of practical training, teams of interviewers and respondents were established that had mock interviews and answered each questionnaire followed with discussion of completed questionnaires, correction of mistakes and amendment of some questions for better comprehension. In addition, training on anthropometric measurements of children under 5 and testing of iodine in salt by testers was conducted in small group. In the frames of the same workshops, special 2-day training workshops were conducted for supervisors and editors on monitoring in the fields and editing of questionnaires. Each participant received Certificate upon completion of the workshop.
Prior to fieldwork, supervisors developed special routes and schedules for teams moving by clusters. Before fieldwork mass media (newspapers, TV and radio) in the fields elucidated MICS targets and terms to population.
The data were collected by 16 teams; each was comprised of six female interviewers, two drivers, one editor and one supervisor - head of team. Qualitative composition of fieldworkers was very high; each team comprised of state servants, supervisors were deputy heads of Oblast/City Statistics Departments, editors - director or deputy director FSE DCC AS RK, interviewers - senior specialists and heads of departments. Special badge with colored photo, full name, MICS and AS RK logos was prepared for each team member.
Fieldwork began in January and concluded in March 2006. In addition to collection answers, MICS teams tested iodine in salt households used for cooking and measured weight and height of children under 5. Details and results of these measurements are presented in the correspondent sections of the report.
Preparatory work and coordination of all structures involved in the Project was agreed with MICS coordinators from the Agency RK on Statistics with close cooperation of UNICEF and UNFPA MICS coordinators.
Central office of RSE DCC of the Agency RK on Statistics dispatched all necessary tools and equipment required for MICS fieldwork ahead of time.
During fieldwork, Project Coordinators had a few monitoring visits to the following Oblasts in accordance with schedule for field teams: Akmola, Karaganda, Mangistau, Atyrau, Almaty, Zhambyl, Kyzylorda and South Kazakhstan. Representative from UNICEF Regional Office (Geneva) took part in monitoring in the first two Oblasts.
Heads of Oblast, city (rayon and rural) Akimates, health workers as well as statisticians provided efficient assistance to MICS teams in the fields. After completion of fieldwork teams presented reports, photo/video materials, comments and suggestions for MICS to the Central Office of AS RK.
Four teams by eight people from each Oblast participated in each workshop, in total 32 people. Training included lectures on interviewing techniques, contents of the questionnaires and mock interviews between trainees in practice interviewing. By the end of the training participants spent two days in practicing interviewing at the venue of training workshops. With the purpose of practical training, teams of interviewers and respondents were established that had mock interviews and answered each questionnaire followed with discussion of completed questionnaires, correction of mistakes and amendment of some questions for better comprehension. In addition, training on anthropometric measurements of children under 5 and testing of iodine in salt by testers was conducted in small group. In the frames of the same workshops, special 2-day training workshops were conducted for supervisors and editors on monitoring in the fields and editing of questionnaires. Each participant received Certificate upon completion of the workshop.
Prior to fieldwork, supervisors developed special routes and schedules for teams moving by clusters. Before fieldwork mass media (newspapers, TV and radio) in the fields elucidated MICS targets and terms to population.
The data were collected by 16 teams; each was comprised of six female interviewers, two drivers, one editor and one supervisor - head of team. Qualitative composition of fieldworkers was very high; each team comprised of state servants, supervisors were deputy heads of Oblast/City Statistics Departments, editors - director or deputy director FSE DCC AS RK, interviewers - senior specialists and heads of departments. Special badge with colored photo, full name, MICS and AS RK logos was prepared for each team member.
Fieldwork began in January and concluded in March 2006. In addition to collection answers, MICS teams tested iodine in salt households used for cooking and measured weight and height of children under 5. Details and results of these measurements are presented in the correspondent sections of the report.
Preparatory work and coordination of all structures involved in the Project was agreed with MICS coordinators from the Agency RK on Statistics with close cooperation of UNICEF and UNFPA MICS coordinators.
Central office of RSE DCC of the Agency RK on Statistics dispatched all necessary tools and equipment required for MICS fieldwork ahead of time.
During fieldwork, Project Coordinators had a few monitoring visits to the following Oblasts in accordance with schedule for field teams: Akmola, Karaganda, Mangistau, Atyrau, Almaty, Zhambyl, Kyzylorda and South Kazakhstan. Representative from UNICEF Regional Office (Geneva) took part in monitoring in the first two Oblasts.
Heads of Oblast, city (rayon and rural) Akimates, health workers as well as statisticians provided efficient assistance to MICS teams in the fields. After completion of fieldwork teams presented reports, photo/video materials, comments and suggestions for MICS to the Central Office of AS RK.
Data Collectors
| Name | Abbreviation |
|---|---|
| The Agency of Statistics of the Republic of Kazakhstan | ASRK |
Questionnaires
Questionnaires
The questionnaires for the Kazakhstan 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, education, child labour, water and sanitation, and salt iodization, with optional modules for child discipline, maternal mortality and durability of housing and Kazakhstan specific modules about UICEF.
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 and union, contraception, and HIV/AIDS knowledge, with optional modules for domestic violence, and sexual (reproductive) behavior and Kazakhstan specific module for Tuberculosis.
The children's questionnaire includes children's characteristics, birth registration and early learning, breastfeeding, care of illness, immunization, and anthropometry, with an optional module for child development.
The questionnaires are based on the MICS3 model questionnaire; however, some Modules were adapted to Kazakhstan (in particular, Education Module, which was considerably changed). English questionnaires were translated into Russian and Kazakh. Questionnaires were pre-tested in Fabrichnyi (Almaty Oblast) and Kordai (Zhambyl Oblast) settlements in November 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 and union, contraception, and HIV/AIDS knowledge, with optional modules for domestic violence, and sexual (reproductive) behavior and Kazakhstan specific module for Tuberculosis.
The children's questionnaire includes children's characteristics, birth registration and early learning, breastfeeding, care of illness, immunization, and anthropometry, with an optional module for child development.
The questionnaires are based on the MICS3 model questionnaire; however, some Modules were adapted to Kazakhstan (in particular, Education Module, which was considerably changed). English questionnaires were translated into Russian and Kazakh. Questionnaires were pre-tested in Fabrichnyi (Almaty Oblast) and Kordai (Zhambyl Oblast) settlements in November 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.
Data entry was conducted by 12 data entry operators in tow shifts, supervised by 2 data entry supervisors, using a total of 7 computers (6 data entry computers plus one supervisors computer). All data entry was conducted at the ASRK 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.
Data entry was conducted by 12 data entry operators in tow shifts, supervised by 2 data entry supervisors, using a total of 7 computers (6 data entry computers plus one supervisors computer). All data entry was conducted at the ASRK 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 | |
|---|---|---|---|
| Shokamanov, Yuriy | The Agency of Statistics of the Republic of Kazakhstan | shok@statbase.kz | www.stat.kz |
| Sissemaliev, Raimbek | UNICEF | rsissemaliev@unicef.org | www.childinfo.org |
| Mussabek, Yerbolat | Kazakhstan Association of Demographers | mussabek@ok.kz | |
| 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 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 ASRK (Vshok@statbase.kz) and UNICEF (rsissemaliev@unicef.org).
Requests for access to the datasets may be made through the website www.childinfo.org.
Requests for access to the datasets may be made through the website www.childinfo.org.
Citation requirements
The Agency of Statistics of the Republic of Kazakhstan. Multiple Indicator Cluster Survey: Household , household listing, women and children's files, 2006 [Computer file]. Almaty, Kazakhstan: The Agency of Statistics of the Republic of Kazakhstan [producer], 2006. Almaty, Kazakhstan: Central Statistical Office and New York: Strategic Information Section, Dvision of Policy and Planning, UNICEF [distributors], 2006.
Access authority
| Name | Affiliation |
|---|---|
| Data access person | The Agency of Statistics of the Republic of Kazakhstan |
Disclaimer and copyrights
Disclaimer
The Agency of Statistics of the Republic of Kazakhstan and UNICEF provides these data to external users without any warranty or responsibility implied. ASRK and UNICEF 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_KAZ_2006_MICS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| The Agency of Statistics of the Republic of Kazakhstan | ASRK | Data producer and customization of generic template | |
| Croft, Trevor | TNC | Blancroft Research International | Producer of generic example |
| Zoric, Aleksandar | SMMRI | Strategic Marketing Research | Data producer and customization of generic template |
| James, Rhiannon | UNICEF | Customization of MICS archive for www.childinfo.org |
Date of Metadata Production
2008-03
DDI Document version
Kazakhstan MICS 2006 UNICEF v0.1
Slightly edited version of UNICEF's DDI ref. DDI-KZK-UNICEF-MICS2006/1.0-v0.3
Slightly edited version of UNICEF's DDI ref. DDI-KZK-UNICEF-MICS2006/1.0-v0.3