Multiple Indicator Cluster Survey 2006
Iraq, 2006
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Reference ID
IRQ_2006_MICS_v01_M
Producer(s)
Central Organization for Statistics and Information Technology, Kurdistan Region Statistics Office, Suleimaniya Statistical Directorate, Ministry of Health
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Mar 21, 2011
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Apr 09, 2018
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Identification
Survey ID Number
IRQ_2006_MICS_v01_M
Title
Multiple Indicator Cluster Survey 2006
Country/Economy
| Name | Country code |
|---|---|
| Iraq | IRQ |
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.
The 2006 Iraq Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Iraq;
- To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals and the goals of A World Fit For Children (WFFC) as a basis for future action;
- To contribute to the improvement of data and monitoring systems in Iraq 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 was customized to the needs of the 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 implemented by the Central Organization for Statistics and Information Technology (COSIT), the Kurdistan Region Statistics Office (KRSO) and Suleimaniya Statistical Directorate (SSD), in partnership with the Ministry of Health (MOH). The survey also received support and assistance of UNICEF and other partners. Technical assistance and training for the surveys 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.
The 2006 Iraq Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Iraq;
- To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals and the goals of A World Fit For Children (WFFC) as a basis for future action;
- To contribute to the improvement of data and monitoring systems in Iraq 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 was customized to the needs of the 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 implemented by the Central Organization for Statistics and Information Technology (COSIT), the Kurdistan Region Statistics Office (KRSO) and Suleimaniya Statistical Directorate (SSD), in partnership with the Ministry of Health (MOH). The survey also received support and assistance of UNICEF and other partners. Technical assistance and training for the surveys 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
2007-11-19
Scope
Notes
The Iraq Multiple Indicator Cluster Survey included the following modules in the questionnaires:
HOUSEHOLD QUESTIONNAIRE : Household Listing, Education, Water and Sanitation, Household Characteristics, Child Labour, Child Discipline, Disability, Salt Iodization
WOMEN'S QUESTIONNAIRE: Marriage, Child Mortality, Birth History, Tetanus Toxoid, Maternal and Newborn Health, Contraception and Unmet Need, Attitude Towards Domestic Violence, HIV/AIDS
CHILDREN'S QUESTIONNAIRE: Birth Registration and Early Learning, Vitamin A, Breastfeeding, Care of Illness, Immunization, Anthropometry
HOUSEHOLD QUESTIONNAIRE : Household Listing, Education, Water and Sanitation, Household Characteristics, Child Labour, Child Discipline, Disability, Salt Iodization
WOMEN'S QUESTIONNAIRE: Marriage, Child Mortality, Birth History, Tetanus Toxoid, Maternal and Newborn Health, Contraception and Unmet Need, Attitude Towards Domestic Violence, HIV/AIDS
CHILDREN'S QUESTIONNAIRE: Birth Registration and Early Learning, Vitamin A, Breastfeeding, Care of Illness, Immunization, Anthropometry
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 |
| Disability | MICS Topics |
| Salt iodization | MICS Topics |
| Women's background | MICS Topics |
| Marriage and union | MICS Topics |
| Child mortality | MICS Topics |
| Birth History | Non standard MICS Topic |
| Tetanus toxoid | MICS Topics |
| Maternal and newborn health | MICS Topics |
| Contraception and unmet need | MICS Topics |
| Attitudes towards domestic violence | 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 |
Coverage
Geographic Coverage
The survey is nationally representative and covers the whole of Iraq.
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. The survey also includes a full birth history listing all chuldren ever born to ever-married women age 15-49 years.
Producers and sponsors
Primary investigators
| Name |
|---|
| Central Organization for Statistics and Information Technology |
| Kurdistan Region Statistics Office |
| Suleimaniya Statistical Directorate |
| Ministry of Health |
Producers
| Name | Affiliation | Role |
|---|---|---|
| UNICEF, Iraq Country Office | UNICEF | Technical assistance |
| Strategic Information Section, Division of Policy and Planning, UNICEF NYHQ | UNICEF | International technical assistance |
| The Pan Arab Project for Family Health | League of Arab States | International technical assistance |
| Measure DHS/ORC MACRO | League of Arab States | International technical assistance |
| Government Steering Commitee | Technical assistance | |
| UN Steering Commitee | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| United Nations Children's Fund | UNICEF |
| Canadian International Development Agency | CIDA |
Sampling
Sampling Procedure
The sample for the Iraq Multiple Indicator Cluster Survey was designed to provide estimates on a large number of indicators on the situation of children and women at the national level; for areas of residence of Iraq represented by rural and urban (metropolitan and other urban) areas; for the18 governorates of Iraq; and also for metropolitan, other urban, and rural areas for each governorate. Thus, in total, the sample consists of 56 different sampling domains, that includes 3 sampling domains in each of the 17 governorates outside the capital city Baghdad (namely, a metropolitan area domain representing the governorate city centre, an other urban area domain representing the urban area outside the governorate city centre, and a rural area domain) and 5 sampling domains in Baghdad (namely, 3 metropolitan areas representing Sadir City, Resafa side, and Kurkh side, an other urban area sampling domain representing the urban area outside the three Baghdad governorate city centres, and a sampling domain comprising the rural area of Baghdad).
The sample was selected in two stages. Within each of the 56 sampling domains, 54 PSUs were selected with linear systematic probability proportional to size (PPS).
\After mapping and listing of households were carried out within the selected PSU or segment of the PSU, linear systematic samples of six households were drawn. Cluster sizes of 6 households were selected to accommodate the current security conditions in the country to allow the surveys team to complete a full cluster in a minimal time. The total sample size for the survey is 18144 households. The sample is not self-weighting. For reporting national level results, sample weights are used.
The sampling procedures are more fully described in the sampling appendix of the final report and can also be found in the list of technical documents within this archive.
(Extracted from the final report: Central Organisation for Statistics & Information Technology and Kurdistan Statistics Office. 2007. Iraq Multiple Indicator Cluster Survey 2006, Final Report. Iraq.)
The sample was selected in two stages. Within each of the 56 sampling domains, 54 PSUs were selected with linear systematic probability proportional to size (PPS).
\After mapping and listing of households were carried out within the selected PSU or segment of the PSU, linear systematic samples of six households were drawn. Cluster sizes of 6 households were selected to accommodate the current security conditions in the country to allow the surveys team to complete a full cluster in a minimal time. The total sample size for the survey is 18144 households. The sample is not self-weighting. For reporting national level results, sample weights are used.
The sampling procedures are more fully described in the sampling appendix of the final report and can also be found in the list of technical documents within this archive.
(Extracted from the final report: Central Organisation for Statistics & Information Technology and Kurdistan Statistics Office. 2007. Iraq Multiple Indicator Cluster Survey 2006, Final Report. Iraq.)
Deviations from the Sample Design
No major deviations from the original sample design were made. One cluster of the 3024 clusters selected was not completed all othe clusters were accessed.
Response Rate
Of the 18144 households selected for the sample, 18123 were found to be occupied. Of these, 17873 were successfully interviewed for a household response rate of 98.6 percent. In the interviewed households, 27564 women (age 15-49 years) were identified. Of these, 27186 were successfully interviewed, yielding a response rate of 98.6 percent. In addition, 16570 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 16469 which correspond to a response rate of 99.4 percent. Overall response rates of 97.3 and 98.0 are calculated for the women's and under-5's interviews respectively.
Weighting
The Iraq Multiple Indicator Cluster Survey sample is not self-weighted. Essentially, by allocating equal numbers of households to each of the sampling domains, different sampling fractions were used in each sampling domain since the size of the sampling domains varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data.
The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling domain:
Wh = 1 / fh
The term fh, the sampling fraction at the h-th stratum, is the product of probabilities of selection at every stage in each sampling domain:
fh = P1h * P2h * P3h
where Pih is the probability of selection of the sampling unit in the i-th stage for the h-th sampling domain.
Since the estimated numbers of households per enumeration area prior to the first stage selection (selection of primary sampling units) and the updated number of households per enumeration area were different, individual sampling fractions for households in each enumeration area (cluster) were calculated. The sampling fractions for households in each enumeration area (cluster) therefore included the probability of selection of the enumeration area in that particular sampling domain and the probability of selection of a household in the sample enumeration area (cluster).
A second component which has to be taken into account in the calculation of sample weights is the level of non-response for the household and individual interviews.
The adjustment for household non-response is equal to the inverse value of:
RR = Number of interviewed households / Number of occupied households listed
After the completion of fieldwork, response rates were calculated for each sampling domain. These were used to adjust the sample weights calculated for each cluster.
Similarly, the adjustment for non-response at the individual level (women and under-5 children) is equal to the inverse value of:
RR = Completed women's (or under-5's) questionnaires / Eligible women (or under-5s)
Numbers of eligible women and under-5 children were obtained from the household listing in the Household Questionnaire in households where interviews were completed.
The unadjusted weights for the households were calculated by multiplying the above factors for each enumeration area. These weights were then standardized (or normalized), one purpose of which is to make the sum of the interviewed sample units equal the total sample size at the national level. Normalization is performed by multiplying the aforementioned unadjusted weights by the ratio of the number of completed households to the total unadjusted weighted number of households. A similar standardization procedure was followed in obtaining standardized weights for the women's and under-5's questionnaires. Adjusted (normalized) weights varied between 0.110 and 3.721 in the 56 sampling domains.
Sample weights (Table SD.4) were appended to all data sets and analyses were performed by weighting each household, woman or under-5 with these sample weights.
(Extracted from the final report Appendix A: Central Organisation for Statistics & Information Technology and Kurdistan Statistics Office. 2007. Iraq Multiple Indicator Cluster Survey 2006, Final Report. Iraq.)
The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling domain:
Wh = 1 / fh
The term fh, the sampling fraction at the h-th stratum, is the product of probabilities of selection at every stage in each sampling domain:
fh = P1h * P2h * P3h
where Pih is the probability of selection of the sampling unit in the i-th stage for the h-th sampling domain.
Since the estimated numbers of households per enumeration area prior to the first stage selection (selection of primary sampling units) and the updated number of households per enumeration area were different, individual sampling fractions for households in each enumeration area (cluster) were calculated. The sampling fractions for households in each enumeration area (cluster) therefore included the probability of selection of the enumeration area in that particular sampling domain and the probability of selection of a household in the sample enumeration area (cluster).
A second component which has to be taken into account in the calculation of sample weights is the level of non-response for the household and individual interviews.
The adjustment for household non-response is equal to the inverse value of:
RR = Number of interviewed households / Number of occupied households listed
After the completion of fieldwork, response rates were calculated for each sampling domain. These were used to adjust the sample weights calculated for each cluster.
Similarly, the adjustment for non-response at the individual level (women and under-5 children) is equal to the inverse value of:
RR = Completed women's (or under-5's) questionnaires / Eligible women (or under-5s)
Numbers of eligible women and under-5 children were obtained from the household listing in the Household Questionnaire in households where interviews were completed.
The unadjusted weights for the households were calculated by multiplying the above factors for each enumeration area. These weights were then standardized (or normalized), one purpose of which is to make the sum of the interviewed sample units equal the total sample size at the national level. Normalization is performed by multiplying the aforementioned unadjusted weights by the ratio of the number of completed households to the total unadjusted weighted number of households. A similar standardization procedure was followed in obtaining standardized weights for the women's and under-5's questionnaires. Adjusted (normalized) weights varied between 0.110 and 3.721 in the 56 sampling domains.
Sample weights (Table SD.4) were appended to all data sets and analyses were performed by weighting each household, woman or under-5 with these sample weights.
(Extracted from the final report Appendix A: Central Organisation for Statistics & Information Technology and Kurdistan Statistics Office. 2007. Iraq Multiple Indicator Cluster Survey 2006, Final Report. Iraq.)
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2006-02 | 2006-06 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
In the South/Centre governorates, groups of three teams were supervised by a local supervisor from the statistical office of each governorate. A central supervisor from the steering committee members and MOH was assigned to each governorate. In Kurdistan Region, groups of three teams were supervised by two local supervisors (one from KRSO/SSD and one from MOH). Two central supervisors from KRSO/SSD and MOH were also assigned to each governorate. A high committee, consisting of members from KRSO/SSD and MOH was also assigned for overall supervision of the survey in Kurdistan. Vehicles were rented by all fieldwork teams (including local, central supervisors and steering committee members) to transport them to the selected clusters.
Fieldwork began in the South/Centre governorates of Iraq in February 2006 and concluded in March 2006. In the Kurdistan Region, fieldwork began in Suleimaniya governorate in April 2006 and was completed in April 2006 while fieldwork was initiated in May 2006 in Erbil/Dohuk governorates and concluded in June 2006.
Fieldwork began in the South/Centre governorates of Iraq in February 2006 and concluded in March 2006. In the Kurdistan Region, fieldwork began in Suleimaniya governorate in April 2006 and was completed in April 2006 while fieldwork was initiated in May 2006 in Erbil/Dohuk governorates and concluded in June 2006.
Questionnaires
Questionnaires
The questionnaires were based on the third round of the Multiple Indicator Cluster survey model questionnaires. From the MICS-3 model English version, the questionnaires were revised and customized to suit local conditions and translated into Arabic and Kurdish languages. The Arabic language version of the questionnaire was pre-tested during January 2006 while the Kurdish language version was pre-tested during March 2006. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.
In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, and measured the weights and heights of children age under-5 years.
In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, and measured the weights and heights of children age under-5 years.
Data Processing
Data Editing
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 5 files (hh - household, hl - household members, wm - women age 15-49, ch - children under 5 bh - women age 15-49)
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
Detailed documentation of the editing of data can be found in the data processing guidelines in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)
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 GenCenStat 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.
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 in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)
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 5 files (hh - household, hl - household members, wm - women age 15-49, ch - children under 5 bh - women age 15-49)
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
Detailed documentation of the editing of data can be found in the data processing guidelines in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)
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 GenCenStat 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.
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 in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)
Other Processing
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.
After transferring all files to SPSS, certain variables were recoded for use as background characteristics in the tabulation of the data, including grouping age, education, geographic areas as needed for analysis. In the process of recoding ages and dates some random imputation of dates (within calculated constraints) was performed to handle missing or "don't know" ages or dates. Additionally, a wealth (asset) index of household members was calculated using principal components analysis, based on household assets, and both the score and quintiles were included in the datasets for use in tabulations.
Data Appraisal
Estimates of Sampling Error
Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2005-2006 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 2005-2006 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 2005-2006 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 2005-2006 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 tables folder.
Sampling errors can be evaluated statistically. The sample of respondents to the 2005-2006 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 2005-2006 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 2005-2006 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 tables folder.
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
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 theresearch objectives 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 COSIT, KRSO and UNICEF.
Ministry of Planning / Central Organization for Statistics and Information Technology (COSIT)
Dr. Mehdi Alalak
Head of COSIT
alalak_mm@yahoo.com
Ministry of Planning / Kurdistan Regional Statistics Office (KRSO)
Dr. Jamal Ameen
Head of KRSO
jrmameen@glam.ac.uk
UNICEF, Iraq Support Centre in Amman
Mary-Louise Eagleton
Chief, Planning, Monitoring & Evaluation
meagleton@unicef.org
Requests for access to the datasets may be made through the website www.childinfo.org.
Ministry of Planning / Central Organization for Statistics and Information Technology (COSIT)
Dr. Mehdi Alalak
Head of COSIT
alalak_mm@yahoo.com
Ministry of Planning / Kurdistan Regional Statistics Office (KRSO)
Dr. Jamal Ameen
Head of KRSO
jrmameen@glam.ac.uk
UNICEF, Iraq Support Centre in Amman
Mary-Louise Eagleton
Chief, Planning, Monitoring & Evaluation
meagleton@unicef.org
Requests for access to the datasets may be made through the website www.childinfo.org.
Citation requirements
The Central Organization for Statistics and Information Technology /The Kurdistan Region Statistics Office, Iraq Multiple Indicator Cluster Survey: Household , household listing, women and children's files, 2005-2006 [Computer file]. Iraq: The Central Organization for Statistics and Information Technology /The Kurdistan Region Statistics Office [producer], 2006. Iraq The Central Organization for Statistics and Information Technology /The Kurdistan Region Statistics Office and New York: Strategic Information Section, Dvision of Policy and Planning, UNICEF [distributors], 2006.
Disclaimer and copyrights
Disclaimer
COSIT, KRSO and UNICEF provide these data to external users without any warranty or responsibility implied. COSIT, KRSO and UNICEF accept no responsibility for the results and/or implications of any actions resulting from the use of these data.
Metadata production
DDI Document ID
DDI_IRQ_2006_MICS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Croft, Trevor | TNC | Blancroft Research International | Producer of generic MICS example |
| James, Rhiannon | UNICEF | Producer of Iraq MICS archive for UNICEF childinfo.org |
Date of Metadata Production
2008-03
DDI Document version
Version 01 - Slightly edited version of UNICEF's DDI ref. DDI-UNICEF-MICS2006-V0.1