NGA-NBS-MICS2-1999-V1.0
Nigeria Multiple Indicator Cluster Survey (MICS2)-1999
Second Round
MICS2-1999
No translation
Name | Country code |
---|---|
Nigeria | NGA |
Multiple Indicator Cluster Survey - Round 2 [hh/mics-2]
As a means of monitoring progress toward the goals and objectives set at the World summit for Children for the year 2000, UNICEF in coordination with WHO, UNDP and other international organizations, developed a core set of 75 indicators of specific aspects of the situation of children. Data on these indicators are collected through a Multiple Indicator Cluster Survey (MICS), a global survey developed by UNICEF to measure the
output, outcome and impact of implementation of country programmes of cooperation.
The first MICS in Nigeria was conducted in 1995 by the Federal Office of Statistics (FOS) now National Bureau of Statistics (NBS) with technical assistance from UNICEF. The Nigeria MICS 1999 represents the second MICS in Nigeria and was designed to provide end-decade information on many of the indicators. As in the previous MICS, the present survey (MICS2) was implemented by the Federal Office of Statistics now National Bureau of Statistics (NBS) with technical assistance from UNICEF.
The 1999 Nigeria Multiple Indicator Cluster Survey has as its primary objectives:
• To provide up-to-date information for assessing the situation of children and women in Nigeria at the end of the decade and for looking forward to the next decade;
• To furnish data needed for monitoring progress toward goals established at the World Summit for Children and a basis for future action;
• To contribute to the improvement of data and monitoring systems in Nigeria and to strengthen technical expertise in the design, implementation, and analysis of such
systems.
The Multiple Indicator Cluster Survey (MICS) is conceptualized to monitor the progress of Child Survival, Development, Protection and Participation (CSPPD) Programmes as well as goals set at the World Summit for Children in 1990. Also, at the World Summit for Social Development in 1995, the need was stressed for better social statistics if social development had to move to centre stage for the cause of the children of the world. In 1995, Federal Office of Statistics (FOS) with technical and funding assistance from UNICEF, institutionalized the Multiple Indicator Survey within the National Integrated Survey of Households (NISH) as a process of collection of regular, reliable and timely social statistics. A technical team, the Multiple Indicator Cluster Survey Intersectoral Task Force (MIT), consisting of all stakeholders was put in place for the 1999 survey to plan, conduct and monitor the survey with FOS providing the leadership. This was an innovation over the previous survey, which greatly enhanced the quality of the work and coverage of programmes.
Nevertheless, this report would have been impossible without the commitments of the following organizations and individuals. Firstly, members of the Multiple Indicator Cluster Survey Inter-sectoral Taskforce (MIT) which facilitated the conduct and over-seeing of the survey. UNICEF Nigeria which gave technical support in the areas of data processing and analysis and report writing through hiring of consultants that worked closely with FOS teams.
This report is another dream to match deeds with words. This report is also unique in the sense that the findings will allow comparison of performance at sub-national (state) and inter national levels. The report will additionally serve as statistical input into future editions of Progress of Nigerian Children Report and UNICEF's State of the World's Children. It is hoped that it will be widely used by various levels of government, Federal and State for programmes and projects monitoring and evaluation on social development and reengineering for the development of the cause of Nigerian Children. It is also an excellent report for top policy formulators and programme managers in the key social sectors.
Sample survey data [ssd]
Household level
Version 1.0 (November, 2009)
2009-11-17
Version 1.0: Data used to generate the tables and the report (2000)
Further editing on the data set released for public use(November, 2009)
The household questionnaire consists of :
Sex
Age
Relationship to headof household
School attendance
Marital status
Literacy and
Occupation.
The household/women’s questionnaire administered in each household and for women aged 15-49.
• Water and sanitation
• Salt iodisation
• Children education
• Fertlity and Child Mortality
• Tetanus Toxoid
• Maternal Mortality
• Care of Acute Respiratory Illness
• Prenatal/Childbirth/Obstetrics, and
• Family Planning
The children’s questionnaire
• Diarrhoea
• Vitamin A
• Malaria
• Breastfeeding
• Immunization
• Child’s Rights, and,
• Anthropometry
Topic | Vocabulary | URI |
---|---|---|
consumption/consumer behaviour [1.1] | CESSDA | http://www.nesstar.org/rdf/common |
economic conditions and indicators [1.2] | CESSDA | http://www.nesstar.org/rdf/common |
income, property and investment/saving [1.5] | CESSDA | http://www.nesstar.org/rdf/common |
rural economics [1.6] | CESSDA | http://www.nesstar.org/rdf/common |
employment [3.1] | CESSDA | http://www.nesstar.org/rdf/common |
basic skills education [6.1] | CESSDA | http://www.nesstar.org/rdf/common |
compulsory and pre-school education [6.2] | CESSDA | http://www.nesstar.org/rdf/common |
post-compulsory education [6.5] | CESSDA | http://www.nesstar.org/rdf/common |
general health [8.4] | CESSDA | http://www.nesstar.org/rdf/common |
health care and medical treatment [8.5] | CESSDA | http://www.nesstar.org/rdf/common |
specific diseases and medical conditions [8.9] | CESSDA | http://www.nesstar.org/rdf/common |
housing [10.1] | CESSDA | http://www.nesstar.org/rdf/common |
children [12.1] | CESSDA | http://www.nesstar.org/rdf/common |
elderly [12.2] | CESSDA | http://www.nesstar.org/rdf/common |
family life and marriage [12.5] | CESSDA | http://www.nesstar.org/rdf/common |
gender and gender roles [12.6] | CESSDA | http://www.nesstar.org/rdf/common |
community, urban and rural life [13.1] | CESSDA | http://www.nesstar.org/rdf/common |
social behaviour and attitudes [13.6] | CESSDA | http://www.nesstar.org/rdf/common |
social conditions and indicators [13.8] | CESSDA | http://www.nesstar.org/rdf/common |
fertility [14.2] | CESSDA | http://www.nesstar.org/rdf/common |
morbidity and mortality [14.4] | CESSDA | http://www.nesstar.org/rdf/common |
Nigeria is Africa's most populous nation with an estimated 1999 population of 124 million. The country is located in West Africa, bordered on the west by the Republic of Benin, on the north by the Republic of Niger and on the East by the Republic of Cameroun. The country occupies a land area of 923, 768 square kilometres and the vegetation ranges from mangrove forest on the coast to desert in the far north.
Administratively, Nigeria consists of 36 states and a Federal Capital territory. These are further divided into 774 local government areas (LGA). For most of her history since independence in 1960, Nigeria has been under military rule. Nigeria returned to democratic rule in May 1999 under a presidential system of government with three tiers of government: federal, state and local. The federal government comprises an executive arm (led by the President), a bicameral legislative arm (Senate and House of Representatives) and a judiciary. Each state has its own governor and house of assembly while each local government has a chairman and council.
The country has abundant natural resources. Major agricultural products include cocoa, rubber, groundnuts, palm oil, cotton, cassava, yam, corn, millet and rice. Mineral resources include petroleum, coal, tin, columbite and gold. However, petroleum has been the mainstay of foreign exchange earnings for Nigeria in the last three decades. Indeed, Nigeria is the sixth largest producer of crude oil in the world and earns several billion US dollars annually from sales of crude oil alone. However, this has not translated to a healthy national economy due to decades of mismanagement and corruption under dictatorial government by successive military regimes. Thus, at the end of the decade (1999), GDP was only US $310. Nigeria's external debt stood at about $32 billion and it was estimated that the government spends about 40% of its earnings servicing foreign debts. The economic hardship during the 1990's meant that social sector spending was far less than required. The health and education sectors, in particular, were deprived of much needed support and funding. It is only with the advent of democratic governance at the end of the decade that the social sector started receiving increased attention.
Nigeria has one of the most ethnically-diverse populations in the world, with more than 380 distinct ethnic groups. The major ethnic groups include (in alphabetical order) the Edo, Efik, Fulani, Hausa, Igbo, Ijaw, Kanuri, Tiv, Urhobo and Yoruba. Population growth has been quite rapid, from 55.7 million in the 1963 national census to 88.5 million in the 1991 census. For much of this period, total fertility rate was over 6 per woman. The population is quite young with 47 percent being under 18 years of age. Children under the age of five years comprise about 20 percent of the population and women of child bearing age another 20 percent of the population.
Under-five mortality has remained over 100 per thousand over the 1990's, being 192 per thousand in 1990 (NDHS 1990) and 147 per thousand in 1995 (MICS 1995). Maternal mortality ratio was estimated to be 800 per thousand in 1995 (The Progress of Nations 1995). Over one-third (36 percent) of under-five children were underweight in 1990. Thus, social indicators show that Nigeria is a country with low GDP, high external debt burden, high child and maternal mortality and high fertility.
2.1 Sample Design
2.1.1 Introduction of NISH Design 1993/99
The Multiple Indicator Cluster Survey (MICS) 1999 was run as a module of the National Integrated Survey of Households (NISH) design. NISH is the Nigerian version of the United Nations National Household Survey Capability Programme and is a multi-subject household based survey system. It is an ongoing programme of household based surveys enquiring into various aspects of households, including housing, health, education and employment. The programme started in 1981 after a pilot study in 1980. The design utilizes a probability sample drawn using a random sampling method at the national and sub-national levels.
The main features of the NISH design are:
Multi-Phase Sampling: In each state 800 EAs were selected with equal probability as first phase samples. A second phase sample of 200 EAs was selected with probability proportional to size.
Multi-Stage Sampling Design: A two-stage design was used. Enumeration Areas were used as the first stage sampling units and Housing Units (HUs) as the second stage sampling units.
Replicated Rotatable Design: Two hundred EAs were selected in each state in 10 independent replicates of 20 EAs per replicate. A rotation was imposed which ensured 6 replicates to be studied each survey year but in subsequent year a replicate is dropped for a new one, that is, a rotation of 1/6 was applied. This means in a survey year, 120 EAs will be covered in each state. In the Federal Capital Territory (Abuja), 60 EAs are covered.
Master Sample: The EAs and HUs selected constitute the Master Sample and subsets were taken for various surveys depending on the nature of the survey and the sample size desired. In any one-year, the 120 EAs are randomly allocated to the 12 months of the year for the survey. The General Household Survey (GHS) is the core module of NISH. Thus, every month 10 EAs are covered for the GHS. For other supplemental modules of NISH, subsets of the master sample are used. The MICS 1999 was run as a module of NISH.
2.1.2 Sample Size
The global MICS design anticipated a sample of 300-500 households per district (domain). This was based on the assumption of a cluster design with design effect of about 2, an average household size of 6, children below the age of 5 years constituting 15 percent of the population and a diarrhoea prevalence of 25 percent. Such a sample would give estimates with an error margin of about 0.1 at the district level. Such a sample would usually come from about 10 clusters of 40 to 50 households per cluster.
In Nigeria, the parameters are similar to the scenario described above. Average household size varied from 3.0 to 5.6 among the states, with a national average of about 5.5. Similarly, children below 5 years constituted between 15-16 percent of total population. Diarrhoea prevalence had been estimated at about 15 percent. These figures have led to sample sizes of between 450 and 660 for each state.
It was decided that a uniform sample of 600 households per state be chosen for the survey. Although non-response, estimated at about 5 percent from previous surveys reduced the sample further, most states had 550 or more households. The MICS sample was drawn from the National Master Sample for the 1998/99 NISH programme implemented by the Federal Office of Statistics (FOS).
The sample was drawn from 30 EAs in each state with a sub-sample of 20 households selected per EA. The design was more efficient than the global MICS design which anticipated a cluster sub-sample size of 40-50 households per cluster. Usually, when the sub-sample size was reduced by half and the number of clusters doubled, a reduction of at least 20 percent in the design effect was achieved. This was derived from DEFF = 1 + (m-1) rho where m is sub-sample size and rho is intra-class correlation. Therefore, the design effect for the Nigerian MICS was about 1.6 instead of 2. This means that for the same size of 600 households, the error margin was reduced by about 10 percent, but where the sample was less than 600 the expected error margin would be achieved.
It should be noted that sampling was based on the former 30 states plus a Federal Capital Territory administrative structure [there are now 36 states and a Federal Capital Territory].
2.1.3 Selection of Households
The global design anticipated either the segmenting of clusters into small areas of approximate 40-45 households and randomly selecting one so that all households within such area was covered or using the random walk procedure in the cluster to select the 40-45 households. Neither of the two procedures was employed. For the segmentation method, it was not difficult to see that the clustering effect could be increased, since, in general, the smaller the cluster the greater the design effect. With such a system, DEFF would be higher than 2, even if minimally. The random walk method, on the other hand, could be affected by enumerator bias, which would be difficult to control and not easily measurable.
For NISH surveys, the listing of all housing units in the selected EAs was first carried out to provide a frame for the sub-sampling. Systematic random sampling was thereafter used to select the sample of housing units. The GHS used a sub-sample of 10 housing units but since the MICS required 20 households, another supplementary sample of 10 housing units was selected and added to the GHS sample. All households in the sample housing units were interviewed, as previous surveys have shown that a housing unit generally contained one household.
Name | Affiliation |
---|---|
National Bureau of Statistics [NBS] | Federal Government of Nigeria(FGN) |
Name | Affiliation | Role |
---|---|---|
United Nations of Children's Fund | UNICEF | Funding & Technical assistance in Stakeholders meetings, monitoring |
Name | Abbreviation | Role |
---|---|---|
National Bureau of Statistics | NBS | Funding |
United Nations of Children's Fund | UNICEF | Funding |
Name | Affiliation | Role |
---|---|---|
Multiple Indicator Cluster Survey Inter-sectoral Taskforce | MIT | Facilitated the conduct and overseeing overseeing of the survey. |
The Multiple Indicator Cluster Survey (MICS) 1999 was run as a module of the National Integrated Survey of Households (NISH) design. NISH is the Nigerian version of the United Nations National Household Survey Capability Programme and is a multi-subject household based survey system. It is an ongoing programme of household based surveys enquiring into various aspects of households, including housing, health, education and employment. The programme started in 1981 after a pilot study in 1980. The design utilizes a probability sample drawn using a random sampling method at the national and sub-national levels.
The main features of the NISH design are:
Multi-Phase Sampling: In each state 800 EAs were selected with equal probability as first phase samples. A second phase sample of 200 EAs was selected with probability proportional to size.
Multi-Stage Sampling Design: A two-stage design was used. Enumeration Areas were used as the first stage sampling units and Housing Units (HUs) as the second stage sampling units.
Replicated Rotatable Design: Two hundred EAs were selected in each state in 10 independent replicates of 20 EAs per replicate. A rotation was imposed which ensured 6 replicates to be studied each survey year but in subsequent year a replicate is dropped for a new one, that is, a rotation of 1/6 was applied. This means in a survey year,
120 EAs will be covered in each state. In the Federal Capital Territory (Abuja), 60 EAs are covered.
Master Sample:
The EAs and HUs selected constitute the Master Sample and subsets were taken for various surveys depending on the nature of the survey and the sample size desired. In any one-year, the 120 EAs are randomly allocated to the 12 months of the year for the survey. The General Household Survey (GHS) is the core module of NISH. Thus, every month 10 EAs are covered for the GHS. For other supplemental modules of NISH, subsets of the master sample are used. The MICS 1999 was run as a module of NISH.
2.1.2 Sample Size
The global MICS design anticipated a sample of 300-500 households per district (domain). This was based on the assumption of a cluster design with design effect of about 2, an average household size of 6, children below the age of 5 years constituting 15 percent of the population and a diarrhoea prevalence of 25 percent. Such a sample would give estimates with an error margin of about 0.1 at the district level. Such a sample would usually come from about 10 clusters of 40 to 50 households per cluster.
In Nigeria, the parameters are similar to the scenario described above. Average household size varied from 3.0 to 5.6 among the states, with a national average of about 5.5. Similarly, children below 5 years constituted between 15-16 percent of total population. Diarrhoea prevalence had been estimated at about 15 percent. These figures have led to sample sizes of between 450 and 660 for each state.
It was decided that a uniform sample of 600 households per state be chosen for the survey. Although non-response, estimated at about 5 percent from previous surveys reduced the sample further, most states had 550 or more households. The MICS sample was drawn from the National Master Sample for the 1998/99 NISH programme implemented by the Federal Office of Statistics (FOS).
The sample was drawn from 30 EAs in each state with a sub-sample of 20 households selected per EA. The design was more efficient than the global MICS design which anticipated a cluster sub-sample size of 40-50 households per cluster. Usually, when the sub-sample size was reduced by half and the number of clusters doubled, a reduction of at least 20 percent in the design effect was achieved. This was derived from DEFF = 1 + (m-1) rho where m is sub-sample size and rho is intra-class correlation. Therefore, the design effect for the Nigerian MICS was about 1.6 instead of 2. This means that for the same size of 600 households, the error margin was reduced by about 10 percent, but where the sample was less than 600 the expected error margin would be achieved.
It should be noted that sampling was based on the former 30 states plus a Federal Capital Territory administrative structure [there are now 36 states and a Federal Capital Territory].
2.1.3 Selection of Households
The global design anticipated either the segmenting of clusters into small areas of approximate 40-45 households and randomly selecting one so that all households within such area was covered or using the random walk procedure in the cluster to select the 40-45 households. Neither of the two procedures was employed. For the segmentation method, it was not difficult to see that the clustering effect could be increased, since, in general, the smaller the cluster the greater the design effect. With such a system, DEFF would be higher than 2, even if minimally. The random walk method, on the other hand, could be affected by enumerator bias, which would be difficult to control and not easily measurable.
For NISH surveys, the listing of all housing units in the selected EAs was first carried out to provide a frame for the sub-sampling. Systematic random sampling was thereafter used to select the sample of housing units. The GHS used a sub-sample of 10 housing units but since the MICS required 20 households, another supplementary sample of 10 housing units was selected and added to the GHS sample. All households in the sample housing units were interviewed, as previous surveys have shown that a housing unit generally contained one household.
There were no deviation from sample Designed
With the design of 30 EAs for each state (with 15 EAs for the Federal Capital Territory) and 20 housing units in each EA, 18,300 households in 915 EAs were expected to be covered overall.
Table 1 shows that 16,962 housing units were sampled of which 15,883 (94 percent) were occupied and respondents from 15,580 households (92 percent of the sampled number) were interviewed. There were no urban-rural differences in response rate.
In the interviewed households, 19,514 eligible women aged 15-49 were identified. Of these, 11,004 had children and thus were eligible for the fertility module interview (Table 3); 10,606 of these 11,004 women were successfully interviewed, yielding a response rate of 96 percent. A total number of 12,072 children under-five were listed in the household questionnaires. Of these, questionnaires were completed for 10,086 children for a response rate of 84 percent.
The Nigeria MICS 1999 design was not self-weighting therefore the need for appropriate weighting in the estimation procedure. Using the following notations:
Ni = No. of total EAs in ith state
ni = No. of total sample EAs in ith state
Mij = No. of housing units in jth EA of ith state.
mij (=20) = No. of selected housing units in jth EA of ith state
Yijk = The observation of the k housing units in jth EA of ith state
Y = å Ni å Mij å Yijk
ni mij
Other estimates were similarly derived. The weighting thus takes care of the disproportionate allocation.
Two types of questionnaires were used for Nigeria MICS 1999, namely, household questionnaires and children questionnaires.
The questionnaires were based on the MICS model questionnaires, which were adapted to be country specific.
An Instruction Manual was developed in line with the model questionnaires to assist interviewers, editors and supervisors on how to
complete and edit questionnaires in the field.
The household questionnaire was actually a combined household and women’s questionnaire and was administered in each household and for women aged 15-49.
Information collected on all household members included
sex,
age,
relationship to head of household,
school attendance,
marital status,
literacy and occupation.
The household/women’s questionnaire contained modules on:
• Children listing
• Water and sanitation
• Salt iodisation
• Children education
• Fertlity and Child Mortality
• Tetanus Toxoid
• Maternal Mortality
• Care of Acute Respiratory Illness
• Prenatal/Childbirth/Obstetrics, and
• Family Planning
The children’s questionnaire was administered in each household for all children under the age of five years. In this case, the questionnaire was administered to the mother or caretaker of the child. The questionnaire for children under age five included modules on:
• Diarrhoea
• Vitamin A
• Malaria
• Breastfeeding
• Immunization
• Child’s Rights, and,
• Anthropometry
The English questionnaire was translated into three major Nigerian languages: Igbo, Hausa and Yoruba. The questionnaires were then back-translated into English by different set of translators to ensure that the qualities of the questions were retained.
The questionnaires were subsequently pretested. Based on the results of the pretest, modifications were made to the wordings and translation of the questionnaires.
Data Entry
The data entry was done manual.
The data entry started with a trial entry by the data entry clerks to acquaint them with the modalities and/or procedures for the data entry after which substantive data entry began. A total of about 30 operators working in two locations were involved. They worked in two groups, one group worked during the day while the other group worked during the night. This arrangement was resorted to in order to ensure efficient use of computer systems and personnel given the erratic electricity supply at the time. The data entry was completed within 2 weeks. Data entry supervisors working under the Data Processing Coordinator supervised data entry at each location.
Data Cleaning
Data entry was followed by trial tabulation to check for and to correct inconsistencies in the data. A frequency check was done on the values of the variables in all the modules to examine quality of the data. All inconsistencies found were reconciled and all errors found were corrected.
UNICEF also provided a Consultant from Macro International, New York, who evaluated the data and all inconsistencies discovered at this stage were also corrected. Analysis similarly benefited from the various workshops organized by the WCARO specifically for MICS 2
Data processing began in March 1999 and draft tables produced by August, 1999. The final tables were produced in September 2001. The delay in producing the final tables was due to the need to conduct extensive data verification and to the necessity to undertake a series of evaluations to ensure consistency and comparability of figures with those of other countries in the region.
Start | End | Cycle |
---|---|---|
1999-02 | 1999-04 | 40 days |
The pretest exercise for MICS 1999 was conducted in November 1998 while the main survey was conducted from February 15 to April 12 1999
Name | Affiliation | Abbreviation |
---|---|---|
National Bureau of Statistics | FGN | NBS |
In order to ensure reliability, acceptability and good quality of data collected, some quality control measures were designed for the survey. One of them was the involvement of the major stakeholders from relevant ministries, agencies and parastatals in the planning and implementation of the survey. This led to the formation of the MICS Inter-Sectoral Task-Force Committee comprising members drawn from ministries and agencies including
Health, Education,
Women Affairs,
Water Resources,
Planned Parenthood
Federation of Nigeria (PPFN),
National Planning Commission,
ILO and UNICEF.
Members met periodically to design and review the questionnaires before the main survey commenced. The members were involved in the monitoring of the survey in some states and carried out independent quality checks in the field. They were also involved in the review of tables generated for the survey and the analysis. Quality control forms such as interviewer assignment sheet, supervisors’ control and assignment sheets were used and retrieval forms were designed to monitor the survey.
Two mobile teams, each consisting of two female enumerators, one supervisor (male or female) and one editor (male or female) carried out fieldwork in each state while one
team worked in the Federal Capital Territory (FCT).
The interviewers were responsible for conducting interviews with eligible respondents, while the supervisors were responsible for the smooth running of the survey in the EAs as well as administrative arrangements. The editors checked the completed questionnaires thoroughly in each EA and they also carried out independent quality checks.
Each team spent two days in each EA and one day for travelling between EAs. A period of 6 weeks was earmarked for covering 30 EAs in each state. Most states were able to meet the deadline for the data collection while it took up to 8 weeks in some states due to boundary disputes in some EAs, some EAs not being accessible during the rainy season or lack of transportation to some EAs.
The fieldwork began in February 1999 and was completed in all the states in April 1999.
MICS 1999 data were processed in 4 stages namely, manual editing and coding, data entry, data cleaning and tabulation.
Manual Processing
Completed questionnaires started arriving at the FOS headquarters two weeks after training in each of the two zones. The records were sent in two batches from each of the zones. The first batch from Southern zone was received on 8th March 1999 while the second batch was received on 5th April 1999. The Northern zone records were received on 22nd March 1999 and 12th April 1999 respectively.Manual processing started with the development of editing/coding guidelines which were used to train the officers on manual editing. The training, which took place in March 1999, involved officers selected from different levels in the office. The guidelines include errors that could be found in the completed questionnaires and how they could be
corrected. These likely errors include omissions, inconsistencies, unreasonable entries, impossible entries, double entries, transcription errors and others found in the questionnaires. After the completion of the training, which lasted for 3 days, the officers were tested and based on their performances,
9 officers were selected as supervisors while 20 officers were made editors. Four key officers on the survey served as co-ordinators.
Data Preparation
The data for MICS 1999 was prepared to meet the criteria of timeliness and quality in a number of unique ways. These include data collection, manual editing, data capture programs and regular meetings of various interest groups. Data for the survey was collected through FOS network of field offices located in the 31 states of the federation, including the Federal Capital Territory (FCT) Abuja and retrieved to the headquarters in Lagos. Upon arrival, the questionnaires were subjected to manual editing by a team of editors (8) headed by group supervisor (2) and coordinators (2). Data entry programs
were written for each questionnaire and the data were captured independently. The data entry version of the questionnaire using EPI Info 6.0 with error checks and skip instructions was prepared to capture the data by the data processing team led by a supervisor and a coordinator. There were also regular meetings of various stakeholders both internal (within FOS) and external (between FOS, UNICEF and/or other agencies) at intervals during the survey to oversee the data preparation.
Thorough training conducted by experienced NBS headquarters staff during zonal training, Close supervision/monitoring during data collection by supervisors, state officers and zonal controllers. Monitoring and quality control by members of Central Technical Committee (CTC) and State Steering Committee (STC)
Organization name | Abbreviation | Affiliation |
---|---|---|
NATIONAL BUREAU OF STATISTICS | NBS | FGN |
United Nations of Children's Fund | UNICEF | UNICEF |
Name | Affiliation | URL | |
---|---|---|---|
National Bureau of Statistics (NBS) | Federal Government of Nigeria (FGN) | http://www.nigerianstat.gov.ng | feedback@nigerianstat.gov.ng |
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
---|---|
yes | The confidentiality of the individual respondent is protected by law (Statistical Act 2007) This is published in the Official Gazette of the Federal republic of Nigeria No. 60 vol. 94 of 11th June 2007. See section 26 para.2. Punitive measures for breeches of confidentiality are outlined in section 28 of the same Act. |
A comprehensive data access policy is been developed by NBS, however section 27 of the Statistical Act 2007outlines the data access obligation of data producers which includes the realease of properly anonymized micro data.
National Bureau of Statistics, Nigeria, Multiple Indicator Cluster Survey-1999-v.1.0
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 for interpretations or inferences based upon such uses.
© NBS 2009
Name | Affiliation | URL | |
---|---|---|---|
Dr V.O. Akinyosoye | Statistician General | voakinyosoye@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
DR G.O. Adewoye | Director Real Sector and Household Statistics Department | georgeadewoye@yahoo.com | http://www.nigerianstat.gov.ng |
Mr E.O. Ekezie | Head of Information and Comnucation Technology Department | eekezie@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Mr E .I. Fafunmi | Data Curator | biyifafunmi@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Mr R.F. Busari | Head (Systems Programming) | rfbusari@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Mrs A. A. Akinsanya | Data Archivist | paakinsanya@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
National Bureau of Statistics (NBS) | Fedral Government of Nigeria (FGN) | feedback@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
DDI-NGA-NBS-MICS2-1999-V1.0
Name | Abbreviation | Affiliation | Role |
---|---|---|---|
National Bureau of Statistics | NBS | Federal Government of Nigeria (FGN) | Metadata Producer |
2009-11-17
Version 1.0 (November, 2009)