Multiple Indicator Cluster Survey 2016-2017
Nigeria, 2016 - 2017
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Reference ID
NGA_2016_MICS_v01_M
Producer(s)
National Bureau of Statistics of Nigeria, United Nations Children’s Fund
Metadata
Created on
May 01, 2018
Last modified
May 01, 2018
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Identification
Survey ID Number
NGA_2016_MICS_v01_M
Title
Multiple Indicator Cluster Survey 2016-2017
Country/Economy
| Name | Country code |
|---|---|
| Nigeria | NGA |
Study type
Multiple Indicator Cluster Survey - Round 5 [hh/mics-5]
Series Information
The first in the series of the Multiple Indicator Cluster Survey (MICS1) in Nigeria was conducted in 1995 by the Federal Office of Statistics (FOS), now National Bureau of Statistics (NBS), with technical and funding assistance from UNICEF. Since then, MICS has been institutionalized within the National Integrated Survey of Households (NISH) in the National Bureau of Statistics, as a process of collecting regular, reliable and timely social statistics. The second and third rounds of MICS were conducted in 1999 and 2007 respectively. The fourth round of MICS conducted in 2011 was better planned and executed than the previous rounds. The 2016-17 round (MICS5) consolidated on the achievement of MICS4 by providing data for more indicators, introduced the use of CAPI device and further raise the quality of the data collected as acknowledged by UNICEF regional and headquarters offices.
The current round of MICS has been expanded in content and scope to include questionnaires for individual men and water quality test. New modules were also introduced such as tobacco and alcohol use, life satisfaction, access to mass media and use of information and communication technology. Another innovation introduced in the MICS 2016-17 also included the pilot testing of further analysis and disaggregation of state data up to senatorial district levels (as can be seen in Lagos and Kano states) with the aim of providing data that can be used for better planning and programming at the grassroots. The climax of the new innovations was the successful combination and implementation of two National surveys (The Multiple Indicator Cluster Survey and the National Immunization Coverage Survey - MICS/NICS) jointly executed together.
Apart from MICS being a major source of data for indicators related to development and improvement of well-being of children, women and men in Nigeria, another key concern of MICS is to improve statistical systems and this is the reason why key players in the Nigeria Statistical Systems participated in the planning and execution of the MICS5.
The current round of MICS has been expanded in content and scope to include questionnaires for individual men and water quality test. New modules were also introduced such as tobacco and alcohol use, life satisfaction, access to mass media and use of information and communication technology. Another innovation introduced in the MICS 2016-17 also included the pilot testing of further analysis and disaggregation of state data up to senatorial district levels (as can be seen in Lagos and Kano states) with the aim of providing data that can be used for better planning and programming at the grassroots. The climax of the new innovations was the successful combination and implementation of two National surveys (The Multiple Indicator Cluster Survey and the National Immunization Coverage Survey - MICS/NICS) jointly executed together.
Apart from MICS being a major source of data for indicators related to development and improvement of well-being of children, women and men in Nigeria, another key concern of MICS is to improve statistical systems and this is the reason why key players in the Nigeria Statistical Systems participated in the planning and execution of the MICS5.
Abstract
The Multiple Indicator Cluster Survey (MICS) is a primary source of information on women and children as it provides statistical indicators that are critical for the measurement of human development. It is an international household survey programme developed by United Nations Children’s Fund (UNICEF). The MICS is designed to collect statistically sound and internationally comparable estimates of key indicators that are used to assess the situation of children and women in the areas of health, education, child protection and HIV/AIDS. It can also be used as a data collection tool to generate data for monitoring the progress towards national goals and global commitments which aimed at promoting the welfare of children and women such as MDGs and SDGs.
OBJECTIVES
The primary objectives of Multiple Indicator Cluster Survey (MICS) Nigeria 2016-17 are:
- To provide up-to-date information for assessing the situation of children and women in Nigeria;
- To generate data for the critical assessment of the progress made in various programme areas, and to identify areas that require more attention;
- To contribute to the generation of baseline data for the SDG;
- To furnish data needed for monitoring progress toward goals established in the post Millennium Declaration and other internationally agreed goals, as a basis for future action;
- To provide disaggregated data to identify disparities among various groups to enable evidence based actions aimed at social inclusion of the most vulnerable.
OBJECTIVES
The primary objectives of Multiple Indicator Cluster Survey (MICS) Nigeria 2016-17 are:
- To provide up-to-date information for assessing the situation of children and women in Nigeria;
- To generate data for the critical assessment of the progress made in various programme areas, and to identify areas that require more attention;
- To contribute to the generation of baseline data for the SDG;
- To furnish data needed for monitoring progress toward goals established in the post Millennium Declaration and other internationally agreed goals, as a basis for future action;
- To provide disaggregated data to identify disparities among various groups to enable evidence based actions aimed at social inclusion of the most vulnerable.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Individuals
- Households
- Households
Version
Version Description
- v01: Edited, anonymous datasets for public distribution.
Scope
Notes
The scope of the Multiple Indicator Cluster Survey includes:
- HOUSEHOLD: List of Household Members, Education, Child Labour, Child Discipline, Household Characteristics, Insecticide Treated Nets, Water and Sanitation, Handwashing, Salt Iodization and Water Quality Test.
- Women: Woman Information Panel, Woman’s Background, Access to Mass Media and Use of Information/Communication Technology, Fertility/Birth History, Desire for Last Birth, Maternal and Newborn Health, Post-natal Health Checks, Illness Symptoms, Use of Contraception, Unmet Need for Contraception, Female Genital Mutilation/Cutting, Attitudes Toward Domestic Violence, Marriage/Union, Sexual Behavior, HIV/AIDS, Tobacco and Alcohol Use and Life Satisfaction.
- Men: Man Information Panel, Man’s Background, Access to Mass Media and Use of Information/Communication Technology, Fertility, Attitudes Toward Domestic Violence, Marriage/Union, Sexual Behavior, HIV/AIDS, Circumcision, Tobacco and Alcohol Use and Life Satisfaction.
- Children: Under Five Information Panel, Age, Birth Registration, Early Childhood Development, Breastfeeding and Dietary Intake, Immunization, Care of Illness and Anthropometry.
- HOUSEHOLD: List of Household Members, Education, Child Labour, Child Discipline, Household Characteristics, Insecticide Treated Nets, Water and Sanitation, Handwashing, Salt Iodization and Water Quality Test.
- Women: Woman Information Panel, Woman’s Background, Access to Mass Media and Use of Information/Communication Technology, Fertility/Birth History, Desire for Last Birth, Maternal and Newborn Health, Post-natal Health Checks, Illness Symptoms, Use of Contraception, Unmet Need for Contraception, Female Genital Mutilation/Cutting, Attitudes Toward Domestic Violence, Marriage/Union, Sexual Behavior, HIV/AIDS, Tobacco and Alcohol Use and Life Satisfaction.
- Men: Man Information Panel, Man’s Background, Access to Mass Media and Use of Information/Communication Technology, Fertility, Attitudes Toward Domestic Violence, Marriage/Union, Sexual Behavior, HIV/AIDS, Circumcision, Tobacco and Alcohol Use and Life Satisfaction.
- Children: Under Five Information Panel, Age, Birth Registration, Early Childhood Development, Breastfeeding and Dietary Intake, Immunization, Care of Illness and Anthropometry.
Coverage
Geographic Coverage
National, rural/urban, states as well as the 6 geo-political zones of Nigeria.
Universe
All household members (usual residents), all women age 15-49 years, all men age 15-49 years and all children under 5 years of age.
Producers and sponsors
Primary investigators
| Name |
|---|
| National Bureau of Statistics of Nigeria |
| United Nations Children’s Fund |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| United Nations International Children's Fund | UNICEF |
| World Health Organization | WHO |
| World Bank | WB |
| Save One Million Live | SOML |
| Bill and Melinda Gates Foundation | |
| United Nations Population Funds | UNFPA |
| United States Agency for International Development | USAID |
Other Identifications/Acknowledgments
| Name | Affiliation |
|---|---|
| National Primary Health Care Development Agency | NPHCDA |
Sampling
Sampling Procedure
SAMPLE SIZE AND SAMPLE ALLOCATION
The sample size for the Nigeria MICS5 was calculated as 37,440 households.
The principal domain of reporting to which the sample size n refers in this calculation is the state. For this sample design, determination of the sample size is based on the indicator stunting prevalence in under-5 children as the design variable. The results from the MICS4 of 2011 reported stunting prevalence at 35.8 percent at the national level. This estimate had a relatively high design effect (deff) of 4.85, indicating a large clustering effect for this characteristic. However, with the more efficient sample design for the MICS 2016-17 it was expected that the deff will be lower, so a value of 3.5 was assumed for the deff in calculating the sample size. The value for pb (percentage of children aged 0-4 years in the total population) based on the results of the MICS4 2011 and NDHS 2013 is 17.1; and Average Size (average household size) is 5.0. For state-level results, it is reasonable to use a relative margin of error (RME) of 18%. Based on previous survey results, the household response rate is assumed to be 95%.
For 34 states and the FCT Abuja a sample of 60 EAs was selected per state and 16 households per EA, which gives a sample size of 960 households in each of these states. Six (6) replicates containing ten (10) EAs/clusters each was selected from the NISH2 master sample for each of these states. In the case of Kano and Lagos States, additional results were needed at the level of the three senatorial districts in each state. Therefore, a sample of 40 EAs per senatorial district was selected in these two states from the NISH2 master sample, for a total of 120 sample EAs and 1,920 sample households in each state. The total sample size for Nigeria was 37,440 households. And the selection of 16 households per EA slightly reduces the design effects compared to the MICS 2011, in which 20 households were selected per EA
SAMPLING FRAME AND SELECTION OF CLUSTERS
The MICS sample clusters were selected from the NISH2 master sample, based on the 2006 census frame. For the NISH2 master sample the census enumeration areas were defined as primary sampling units (PSUs), stratified by state. The first stage of sampling for MICS was completed by selecting the required number of enumeration areas from the NISH2 master sample for each of the 36 states of the federation and FCT Abuja which cut across urban and rural areas.
LISTING ACTIVITIES
Since the sampling frame (the 2006 Census) was not up-to-date, a new listing of households was conducted in November 2015 for all the sample enumeration areas prior to the selection of households. For this purpose, listing teams were formed who visited all of the selected enumeration areas and listed all households in each enumeration area. Selected staff of the National Bureau of Statistics (NBS) in all the states carried out the listing exercise. Six (6) teams were constituted that carried out the listing exercise in each state except Lagos and Kano where twelve teams were constituted respectively. Each team comprises of 2 enumerators and one (1) supervisor who supervised two (2) teams. There were three (3) supervisors in each of the 35 states, and six (6) supervisors for Lagos and Kano states respectively. The listing exercise lasted for twelve (12) days. Out of the 2,340 enumeration areas selected for the household listing, one hundred and one (101) of them were not visited because they were inaccessible due to insecurity during the listing exercise.
SELECTION OF HOUSEHOLDS
Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to N (the total number of households in each enumeration area) at the National Bureau of Statistics (Field Services and Methodology Department), where the selection of 16 households in each enumeration area was carried out using random systematic selection procedures.
The survey also included a questionnaire for individual men aged 15 to 49 years. It was administered in eight out of sixteen sampled households. Households with even number in each sample cluster were selected and all eligible men were interviewed.
Within each state, a sub-sample of 30 enumeration areas was systematically selected for the water quality test. In each of these sampled EAs, a systematic sub sample of three households out of sixteen (16) MICS sample households was selected for the water quality tests.
The sample size for the Nigeria MICS5 was calculated as 37,440 households.
The principal domain of reporting to which the sample size n refers in this calculation is the state. For this sample design, determination of the sample size is based on the indicator stunting prevalence in under-5 children as the design variable. The results from the MICS4 of 2011 reported stunting prevalence at 35.8 percent at the national level. This estimate had a relatively high design effect (deff) of 4.85, indicating a large clustering effect for this characteristic. However, with the more efficient sample design for the MICS 2016-17 it was expected that the deff will be lower, so a value of 3.5 was assumed for the deff in calculating the sample size. The value for pb (percentage of children aged 0-4 years in the total population) based on the results of the MICS4 2011 and NDHS 2013 is 17.1; and Average Size (average household size) is 5.0. For state-level results, it is reasonable to use a relative margin of error (RME) of 18%. Based on previous survey results, the household response rate is assumed to be 95%.
For 34 states and the FCT Abuja a sample of 60 EAs was selected per state and 16 households per EA, which gives a sample size of 960 households in each of these states. Six (6) replicates containing ten (10) EAs/clusters each was selected from the NISH2 master sample for each of these states. In the case of Kano and Lagos States, additional results were needed at the level of the three senatorial districts in each state. Therefore, a sample of 40 EAs per senatorial district was selected in these two states from the NISH2 master sample, for a total of 120 sample EAs and 1,920 sample households in each state. The total sample size for Nigeria was 37,440 households. And the selection of 16 households per EA slightly reduces the design effects compared to the MICS 2011, in which 20 households were selected per EA
SAMPLING FRAME AND SELECTION OF CLUSTERS
The MICS sample clusters were selected from the NISH2 master sample, based on the 2006 census frame. For the NISH2 master sample the census enumeration areas were defined as primary sampling units (PSUs), stratified by state. The first stage of sampling for MICS was completed by selecting the required number of enumeration areas from the NISH2 master sample for each of the 36 states of the federation and FCT Abuja which cut across urban and rural areas.
LISTING ACTIVITIES
Since the sampling frame (the 2006 Census) was not up-to-date, a new listing of households was conducted in November 2015 for all the sample enumeration areas prior to the selection of households. For this purpose, listing teams were formed who visited all of the selected enumeration areas and listed all households in each enumeration area. Selected staff of the National Bureau of Statistics (NBS) in all the states carried out the listing exercise. Six (6) teams were constituted that carried out the listing exercise in each state except Lagos and Kano where twelve teams were constituted respectively. Each team comprises of 2 enumerators and one (1) supervisor who supervised two (2) teams. There were three (3) supervisors in each of the 35 states, and six (6) supervisors for Lagos and Kano states respectively. The listing exercise lasted for twelve (12) days. Out of the 2,340 enumeration areas selected for the household listing, one hundred and one (101) of them were not visited because they were inaccessible due to insecurity during the listing exercise.
SELECTION OF HOUSEHOLDS
Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to N (the total number of households in each enumeration area) at the National Bureau of Statistics (Field Services and Methodology Department), where the selection of 16 households in each enumeration area was carried out using random systematic selection procedures.
The survey also included a questionnaire for individual men aged 15 to 49 years. It was administered in eight out of sixteen sampled households. Households with even number in each sample cluster were selected and all eligible men were interviewed.
Within each state, a sub-sample of 30 enumeration areas was systematically selected for the water quality test. In each of these sampled EAs, a systematic sub sample of three households out of sixteen (16) MICS sample households was selected for the water quality tests.
Response Rate
Out of 37,440 households sampled, 35,747 households were visited, 34,289 were found to be occupied and 33,901 were successfully interviewed, representing a household response rate of 98.9 percent.
In the interviewed households, 36,176 women (age 15-49 years) were identified. Of these, 34,376 were successfully interviewed, yielding a response rate of 95.0 percent within the interviewed households.
The survey also sampled men (age 15-49), but required only a subsample. All men (age 15-49) were identified in 17,868 households selected for the men questionnaire; 16,514 men (age 15-49 years) were listed in the household questionnaires. Questionnaires were completed for 15,183 eligible men, which corresponds to a response rate of 91.9 percent within eligible interviewed households.
There were 28,578 children under age five listed in the household questionnaires. Questionnaires were completed for 28,085 of these children, which corresponds to a response rate of 98.3 percent within interviewed households.
Overall response rates of 93.9, 90.9 and 97.2 are calculated for the individual interviews of women, men, and under-5s, respectively.
In the interviewed households, 36,176 women (age 15-49 years) were identified. Of these, 34,376 were successfully interviewed, yielding a response rate of 95.0 percent within the interviewed households.
The survey also sampled men (age 15-49), but required only a subsample. All men (age 15-49) were identified in 17,868 households selected for the men questionnaire; 16,514 men (age 15-49 years) were listed in the household questionnaires. Questionnaires were completed for 15,183 eligible men, which corresponds to a response rate of 91.9 percent within eligible interviewed households.
There were 28,578 children under age five listed in the household questionnaires. Questionnaires were completed for 28,085 of these children, which corresponds to a response rate of 98.3 percent within interviewed households.
Overall response rates of 93.9, 90.9 and 97.2 are calculated for the individual interviews of women, men, and under-5s, respectively.
Weighting
The Nigeria MICS sample is not self-weighting. Essentially, by allocating equal numbers of sample households to each of the states, different sampling fractions were used in each state since the sizes of the states varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data.
The basic weight for each sample household is equal to the inverse of its probability of selection (calculated by multiplying the probabilities at each sampling stage).
The first component of this probability corresponds to the LGA master sample and the second component corresponds to the NISH2 master sample.
In the case of the states of Kano and Lagos, the NISH2 master sample EAs were stratified by senatorial district and the EAs were selected separately within each senatorial district.
Since the updated number of households in the listing varies by sample enumeration area, individual overall probability of selection for households in each sample enumeration area (cluster) was calculated.
It is also important to adjust the basic weights for the households to take into account the non-response at the stratum level.
After the completion of fieldwork, response rates were calculated for each sampling stratum. These were used to adjust the sample weights calculated for each cluster.
Following the adjustment of the raw household weights for non-response, these weights are generally normalized (standardized) so that relative weights are used for the analysis of the survey data. In this way the sum of the relative weights is equal to the number of sample households at the national level. The household weights were normalized by dividing each weight by the average weight at the national level (that is, the sum of the weights for all sample households divided by the number of sample households).
Given that sometimes it is not possible to complete a woman questionnaire for each eligible woman identified in a sample household, it is also necessary to have a separate woman weight with an additional nonresponse adjustment factor applied to the household weight at the stratum level.
There were cases where a child questionnaire was not completed for all the children under 5 years in some sample households. Therefore, a separate child weight with an additional non-response adjustment factor applied to the adjusted household weight was used.
The weights for the men questionnaires were calculated in the same way as the women weights, except that the raw household weight was multiplied by 2, since half of the sample households were selected for the men’s questionnaires. In this case the number of sample men in the numerator and denominator of the non-response adjustment factor was based only on the sample households selected for the men’s questionnaires.
The non-response adjustment factors for the individual women, men, and under-5 questionnaires were applied to the adjusted household weights. Numbers of eligible women, men, and under-5 children were obtained from the roster of household members in the Household Questionnaire for households where interviews were completed.
The women, men and child weights are normalized in the same way as the household weights. In this case the full (raw) weights were divided by the average women, men or child weight, respectively.
Sample weights were appended to all data sets and analyses were performed by weighting households, women, men, or under-5s with these sample weights.
The basic weight for each sample household is equal to the inverse of its probability of selection (calculated by multiplying the probabilities at each sampling stage).
The first component of this probability corresponds to the LGA master sample and the second component corresponds to the NISH2 master sample.
In the case of the states of Kano and Lagos, the NISH2 master sample EAs were stratified by senatorial district and the EAs were selected separately within each senatorial district.
Since the updated number of households in the listing varies by sample enumeration area, individual overall probability of selection for households in each sample enumeration area (cluster) was calculated.
It is also important to adjust the basic weights for the households to take into account the non-response at the stratum level.
After the completion of fieldwork, response rates were calculated for each sampling stratum. These were used to adjust the sample weights calculated for each cluster.
Following the adjustment of the raw household weights for non-response, these weights are generally normalized (standardized) so that relative weights are used for the analysis of the survey data. In this way the sum of the relative weights is equal to the number of sample households at the national level. The household weights were normalized by dividing each weight by the average weight at the national level (that is, the sum of the weights for all sample households divided by the number of sample households).
Given that sometimes it is not possible to complete a woman questionnaire for each eligible woman identified in a sample household, it is also necessary to have a separate woman weight with an additional nonresponse adjustment factor applied to the household weight at the stratum level.
There were cases where a child questionnaire was not completed for all the children under 5 years in some sample households. Therefore, a separate child weight with an additional non-response adjustment factor applied to the adjusted household weight was used.
The weights for the men questionnaires were calculated in the same way as the women weights, except that the raw household weight was multiplied by 2, since half of the sample households were selected for the men’s questionnaires. In this case the number of sample men in the numerator and denominator of the non-response adjustment factor was based only on the sample households selected for the men’s questionnaires.
The non-response adjustment factors for the individual women, men, and under-5 questionnaires were applied to the adjusted household weights. Numbers of eligible women, men, and under-5 children were obtained from the roster of household members in the Household Questionnaire for households where interviews were completed.
The women, men and child weights are normalized in the same way as the household weights. In this case the full (raw) weights were divided by the average women, men or child weight, respectively.
Sample weights were appended to all data sets and analyses were performed by weighting households, women, men, or under-5s with these sample weights.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2016-09 | 2017-01 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
Training for the fieldwork was conducted for thirty-one (31) days in August 2016. Training included lectures on interviewing techniques and contents of the questionnaires. Mock interviews among trainees were also conducted to gain practice in asking questions. Towards the end of the training period, trainees spent 2 days in field practice in purposively selected residential areas in 2 communities in each of the 6 training locations in Keffi (Nasarawa state), Gombe (Gombe state), Kano (Kano state), Enugu (Enugu state), Ikeja (Lagos state) and Calabar (Cross River state).
The data were collected by 78 teams; each team comprised four interviewers, one driver, one measurer and a supervisor. Fieldwork began in September 2016 and concluded in January 2017.
Using Computer Assisted Personal Interviewing (CAPI), the data were electronically captured from the field and transmitted to a central server, using CSPro CAPI application, Version 5.0. Being the first time of using CAPI, the programme was pretested to know the effectiveness and efficiency of the device. Using CAPI to captured data helps in reducing error associated with paper questionnaire such as omission and skipping errors.
The data were collected by 78 teams; each team comprised four interviewers, one driver, one measurer and a supervisor. Fieldwork began in September 2016 and concluded in January 2017.
Using Computer Assisted Personal Interviewing (CAPI), the data were electronically captured from the field and transmitted to a central server, using CSPro CAPI application, Version 5.0. Being the first time of using CAPI, the programme was pretested to know the effectiveness and efficiency of the device. Using CAPI to captured data helps in reducing error associated with paper questionnaire such as omission and skipping errors.
Questionnaires
Questionnaires
The questionnaires are based on the MICS5 questionnaire3 model (English version), customized and pre-tested in Cross River, Enugu, Gombe, Lagos, Kaduna, Kano, Nasarawa and Oyo states in April 2016. Based on the results of the pre-test, modifications were made to the wording of the questionnaires. A copy of the Nigeria MICS questionnaires is provided as Related Material.
In addition to the administration of questionnaires, salt iodization and water quality tests were conducted. Weight and height of children age under 5 years were also measured.
In addition to the administration of questionnaires, salt iodization and water quality tests were conducted. Weight and height of children age under 5 years were also measured.
Data Processing
Data Editing
Data were analyzed using the Statistical Package for Social Scientists (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF MICS team were customized and used for this purpose.
Data Appraisal
Estimates of Sampling Error
The sample of respondents selected in the Multiple Indicator Cluster Survey (MICS) 2016 is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data.
The following sampling error measures are presented in this appendix for each of the selected indicators:
- Standard error (se): Standard error is the square root of the variance of the estimate. For survey indicators that are means, proportions or ratios, the Taylor series linearization method is used for the estimation of standard errors. For more complex statistics, such as fertility and mortality rates, the Jackknife repeated replication method is used for standard error estimation.
- Coefficient of variation (se/r) is the ratio of the standard error to the value (r) of the indicator, and is a measure of the relative sampling error.
- Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling based on the same sample size. The square root of the design effect (deft) is used to show the efficiency of the sample design in relation to the precision. A deft value of 1.0 indicates that the sample design of the survey is as efficient as a simple random sample for a particular indicator, while a deft value above 1.0 indicates an increase in the standard error due to the use of a more complex sample design.
- Confidence limits are calculated to show the interval which contains the true value of the indicator for the population, with a specified level of confidence. For MICS results 95% confidence intervals are used, which is the standard for this type of survey. The concept of the 95% confidence interval can be understood in this way: if many repeated samples of identical size and design were taken and the confidence interval computed for each sample, then 95% of these intervals would contain the true value of the indicator.
For the calculation of sampling errors from MICS data, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack have been used.
The following sampling error measures are presented in this appendix for each of the selected indicators:
- Standard error (se): Standard error is the square root of the variance of the estimate. For survey indicators that are means, proportions or ratios, the Taylor series linearization method is used for the estimation of standard errors. For more complex statistics, such as fertility and mortality rates, the Jackknife repeated replication method is used for standard error estimation.
- Coefficient of variation (se/r) is the ratio of the standard error to the value (r) of the indicator, and is a measure of the relative sampling error.
- Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling based on the same sample size. The square root of the design effect (deft) is used to show the efficiency of the sample design in relation to the precision. A deft value of 1.0 indicates that the sample design of the survey is as efficient as a simple random sample for a particular indicator, while a deft value above 1.0 indicates an increase in the standard error due to the use of a more complex sample design.
- Confidence limits are calculated to show the interval which contains the true value of the indicator for the population, with a specified level of confidence. For MICS results 95% confidence intervals are used, which is the standard for this type of survey. The concept of the 95% confidence interval can be understood in this way: if many repeated samples of identical size and design were taken and the confidence interval computed for each sample, then 95% of these intervals would contain the true value of the indicator.
For the calculation of sampling errors from MICS data, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack have been used.
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.
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example,
National Bureau of Statistics (NBS), United Nations Children’s Fund (UNICEF). Nigeria - Multiple Indicator Cluster Survey (MICS) 2016-2017, Ref. NGA_2016_MICS_v01_M. Dataset downloaded from [url] on [date].
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example,
National Bureau of Statistics (NBS), United Nations Children’s Fund (UNICEF). Nigeria - Multiple Indicator Cluster Survey (MICS) 2016-2017, Ref. NGA_2016_MICS_v01_M. Dataset downloaded from [url] on [date].
Access authority
| Name | URL | |
|---|---|---|
| UNICEF | mics@unicef.org | Link |
Location of Data Collection
UNICEF
Archive where study is originally stored
UNICEF
http://mics.unicef.org/surveys
Cost: None
http://mics.unicef.org/surveys
Cost: None
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Metadata production
DDI Document ID
DDI_NGA_2016_MICS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2018-04-30
DDI Document version
Version 01 (April 2018)