{"doc_desc":{"idno":"DDI_NGA_2007_GHS_v01_EN_M_v01_A_OCS_FAO","producers":[{"name":"Office of Chief Statistician","abbreviation":"OCS","affiliation":"Food and Agricultural Organization","role":"Metadata adapted for FAM"},{"name":"National Bureau of Statistics","abbreviation":"NBS","affiliation":"Federal Government of Nigeria (FGN)","role":" Metadata Producer"}],"version_statement":{"version":"NGA_2007_GHS_v01_EN_M_v01_A_OCS_v01"}},"study_desc":{"title_statement":{"idno":"NGA_2007_GHS_v01_EN_M_v01_A_OCS","title":"General  Household Survey, 2007","alt_title":"GHS 2007"},"authoring_entity":[{"name":"National Bureau of Statistics  (NBS)","affiliation":"Federal Government of Nigeria (FGN)"}],"oth_id":[{"name":"Nigerian Commnications Commision","affiliation":"NCC","email":"","role":"Collaborating"}],"production_statement":{"producers":[{"name":"Central Bank of Nigeria","affiliation":"FGN","role":"Collaboration"},{"name":"Nigerian Communication Commission","affiliation":"FGN","role":"Collaboration"}],"copyright":"\u00a9 NBS 2009","funding_agencies":[{"name":"National Bureau of Statistics","abbreviation":"NBS","role":"Funding"},{"name":"Central  Bank of Nigeria","abbreviation":"CBN","role":"Funding"}]},"distribution_statement":{"contact":[{"name":"Dr V.O. Akinyosoye","affiliation":"Statistician General","email":"voakinyosoye@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"DR G.O. Adewoye","affiliation":"Director Real Sector and Household Statistics Department","email":"georgeadewoye@yahoo.com","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Mr E.O. Ekezie","affiliation":"Head of  Information and Comnucation Technology Department","email":"eekezie@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Mr E .I. Fafunmi","affiliation":"Data Curator","email":"biyifafunmi@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Mr R.F. Busari","affiliation":"Head (Systems Programming)","email":"rfbusari@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Mrs A. A. Akinsanya","affiliation":"Data Archivist","email":"paakinsanya@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"National Bureau of Statistics (NBS)","affiliation":"Fedral Government of Nigeria (FGN)","email":"feedback@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"}]},"series_statement":{"series_name":"Other Household Survey [hh\/oth]","series_info":"This General Household Survey (GHS) is the 4th in the series of Collaborative effort of the National Bureau of Statistics (NBS), Central Bank of Nigeria (CBN) and the Nigeria Communications Commission previously conducted in 2004, 2005, 2006 and 2007 being the current one.  However the GHS is a regular survey of the National Bureau of Statistics conducted on quarterly basis before the collaboration was initiated"},"study_info":{"topics":[{"topic":"economic conditions and indicators [1.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"economic policy [1.3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"income, property and investment\/saving [1.5]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"rural economics [1.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"agricultural, forestry and rural industry [2.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"business\/industrial management and organisation [2.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"employment [3.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"labour relations\/conflict [3.3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"retirement [3.4]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"unemployment [3.5]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"working conditions [3.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"basic skills education [6.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"compulsory and pre-school education [6.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"vocational education [6.7]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"childbearing, family planning and abortion [8.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"general health [8.4]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"natural resources and energy [9.3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"housing [10.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"children [12.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"family life and marriage [12.5]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"gender and gender roles [12.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"social and occupational mobility [12.8]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"community, urban and rural life [13.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"specific social services: use and provision [15.3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"information technology [16.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"}],"abstract":"The General Household Survey is a brainchild of the National Bureau of Statistics (NBS) and is often referred to as a regular survey carried out on quarterly basis by the NBS over the years. In recent times, starting from 2004 to be precise, there is a collaborative effort between the NBS and the CBN in 2004 and 2005 and in 2006 the collaboration incorporated Nigerian Communications commission (NCC). \n\nThe main reason for conducting the survey was to enable the collaborating agencies fulfil their mandate in the production of current and credible statistics, to monitor and evaluate the status of the economy and the various government programmes such as the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals (MDGs).  \n\nThe collaborative survey also assured the elimination of conflicts in data generated by the different agencies and ensured a reliable, authentic national statistics for the country.","coll_dates":[{"start":"2008-03-31","end":"2008-04-19","cycle":"20 days"}],"nation":[{"name":"Nigeria","abbreviation":"NGA"}],"geog_coverage":"National Coverage","analysis_unit":"Household","universe":"Household","data_kind":"Sample survey data [ssd]","notes":"Part A: Identification code, Response status, Housing characteristics\/amenities and Information communication Technology (ICT).\nPart B:\tSocio-demographic characteristics and Labour force characteristics\nPart C:\tInformation about the people in the household who were absent during the period of the survey.\nPart D:\tFemale contraceptive only, and children ever born by mothers aged 15 years and above\nPart E:\tBirths of children in the last 12 months, and trained birth attendant used during child delivery.\nPar  F:\tImmunization of children aged 1 year or less and records of their vaccination\nPart G:\tChild nutrition, exclusive breast feeding and length of breast feeding.\nPart H:\tDeaths in the last 12 months, and causes of such deaths.\nPart I:\tHealth of all members, of the household and health care providers.\nPart J:\tHousehold enterprises, income and profit made from such activities.\nPart K:\tHousehold expenditure, such as school fees, medical expenses, housing expenses, remittance, cloth expenses, transport expenses and food expenses."},"method":{"data_collection":{"sampling_procedure":"The GHS was implemented as a NISH module. Six replicates were studied per state including the FCT, Abuja. With a fixed-take of 10 HUs systematically selected per EA, 600 HUs thus were selected for interview per state including the FCT, Abuja.  Hence, nationally, a total of 22,200 HUs were drawn from the 2,220 EAs selected for interview for the GHS.  The selected EAs (and hence the HUs) cut across the rural and urban sectors.  \n\nThe General Household Survey and the National Agricultural Sample Survey designs derived from NBS 2007\/12 NISH sample design. The 2007\/12 NISH sample design is a 2-stage, replicated and rotated cluster sample design with Enumeration Areas (EAs) as first stage sampling units or Primary Sampling Units (PSUs) while  Housing Units constituted the second stage units (secondary sampling units).  The housing units were the Ultimate Sampling Units for the multi-subject survey.\n\nFirst Stage Selection:\nGenerally, the NISH Master Sample in each state is made up of 200 EAs drawn in 20 replicates. A replicate consists of 10 EAs. Replicates 4 - 9, subsets of the Master Sample were studied for modules of the NISH. Sixty EAs were selected with equal probability from the list of EAs in each state of the federation and FCT, Abuja.\n\nSecond Stage Selection:\nIn each selected EA, a listing of housing units was carried out. The result provided the frame for the second stage selection. Ten housing units were selected systematically in each EA after the completion of the listing exercise.  Thereafter, all the households within the selected HUs were interviewed using GHS questionnaire.\n\nAt EAs level, out of the expected 2,220 EAs 2,204 were covered (by the table on page 177 of the report) and\nTABLE 1.6 RETRIEVAL STATUS OF GHS RECORDS.\n\nAt housing units level, out of the 22,200 expected to be covered, 21,796 were canvassed. (same as above) \n\nAS PER DATA SET\nAt EAs level, out of the expected 2,220 EAs  2,204 were covered.\nAt housing units level, out of the 22,200 expected to be covered, 18,355 were canvassed.","sampling_deviation":"Variance Estimate (Jackknife Method)\nEstimating variances using the Jackknife method will require forming replicate from the full sample by randomly eliminating one sample cluster [Enumeration Area (EA) at a time from a state containing k EAs, k replicated estimates are formed by eliminating one of these, at a time, and increasing the weight of the remaining (k-1) EAs by a factor of k\/(k-1).  This process is repeated for each EA.\n\nFor a given state or reporting domain, the estimate of the variance of a rate, r, is given by \n                                        k\nVar(r ) = (Se)2 =   1          S (ri - r)2 \n                         k(k-1)    i=1\n\nwhere (Se) is the standard error, \nk is the number of EAs in the state or reporting domain.\n\nr is the weighted estimate calculated from the entire sample of EAs in the state or reporting domain.  \n\tri  = kr  - (k - 1)r(i), where\n\nr(i) is the re-weighted estimate calculated from the reduced sample of k-1 EAs.\n\nTo obtain an estimate of the variance at a higher level, say, at the national level, the process is repeated over all states, with k redefined to refer to the total number of EAs (as opposed to the number in the states).","coll_mode":"Face-to-face [f2f]","research_instrument":"The questionnaire for the GHS is a structured questionnaire based on household characteristics with some modifications and additions. The House project module is a new addition and some new questions on ICT.\n\nThe questionnaires were scaned.\n\nThis section were divided into eleven parts.\n\nPart A: Identification code, Response status, Housing characteristics\/amenities and Information communication Technology (ICT).\nPart B:\tSocio-demographic characteristics and Labour force characteristics\nPart C:\tInformation about the people in the household who were absent during the period of the survey.\nPart D:\tFemale contraceptive only, and children ever born by mothers aged 15 years and above\nPart E:\tBirths of children in the last 12 months, and trained birth attendant used during child delivery.\nPart F:\tImmunization of children aged 1 year or less and records of their vaccination\nPart G:\tChild nutrition, exclusive breast feeding and length of breast feeding.\nPart H:\tDeaths in the last 12 months, and causes of such deaths.\nPart I:\tHealth of all members, of the household and health care providers.\nPart J:\tHousehold enterprises, income and profit made from such activities.\nPart K:\tHousehold expenditure, such as school fees, medical expenses, housing expenses, remittance, cloth expenses, transport expenses and food expenses.","coll_situation":"Prior to the commencement of data collection, training was conducted at two levels; training of trainers and zonal level trainings. This training was to equip trainers and trainees with background information about the survey and what is expected of them. Also, training sessions included classroom teaching, demonstration, mock interviews, role playing, field and home exercises.  \n\nThe General Household Survey (GHS) is a household based exercise. In each state, 3 teams were used comprising 3 supervisors and 12 enumerators. A team was made up of one supervisor and four enumerators.  \n\nEach team covered 20 Enumeration Areas for a period of 20 days. A pair of enumerators in a team covered 10 EAs. This translated to covering an Enumeration Area for an average of 4 days for the different statistical operations.  Each team moved in a roving manner.","weight":"The variable (Hweight ) Household weight is computed and attached to the data file.\n\nThe formula adopted in calculating the design weights for the survey data (sample results) were as follows:\n(i)\tThe probability of selecting an EA within a state was obtained by dividing the total number of EAs sampled in a state by total number of EAs in that particular state. Let this be represented by fj. That is,\n fj      = \tTotal Number of EAs sampled in a state\n\t\tTotal Number of EAs in that particular State \n\n(ii)\tLikewise, the probability of selecting an housing unit (HU) within an EA was obtained by dividing the total number of housing units selected in an EA  by the total number of housing units (HUs) listed in that particular EA. Let this be represented by fk. That is,\nfk     = \t Total Number of HUs selected in an EA\n Total Number of HUs listed in that particular EA\nMathematically,\nDesign weight =     Total number of EAs in a state\n\t\t                    Total number of EAs sampled in that particular state\n\t\t\t\t\t\tX\n\t\t\t        Total Number of HUs listed in an EA \n\t\t\t        Total Number of HUs selected in that particular EA\n\nEstimation Procedures:\nLet the probability of selecting the EA be fj and the probability of selecting the housing unit be fk.  Then the product f = fjfk =  1  where fj = n and fk = h\n                                                                 Wj k                N              H.\n\nHousehold Weight  (HHWeight )\n\n\t\t\n  \t                  n\t       h\n\tYs =  \tN   ?    H  ?  X sj k\n\t\t n  j=1   h k=1\n\n                                 n      h\n\t     =\tN   H   ?     ?  X sj k\n\t\tn     h    j=1  k=1\n\n                                                   n       h\n                \t=\tW s j k       ?       ?   X sj k        (Note: W s j k = N . H )\n\t\t                 j = 1  k=1                                                    n     h   \n\tWhere:\n\t\u02c6\n\tYs\t=\tEstimate for states\nN  \t=\tTotal Number of EAs in states\nn  \t=\tSelected number of EAs in states\nH \t= \tTotal number of Housing Units listed in the jth EA \t  \nh  \t=\tSelected number of Housing Units in the jth EA.\nXsj k  \t=\tValue of the element in the kth housing unit of jth EA in states.  \nWsjk\t=\tWeight of the element in kth housing unit of the jth EA in states.","cleaning_operations":"The data editing is in 2 phases namely manual editing before the questionnaires were scanned.\nThis involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire.\n \nThe second editing is the computer editing, this is the cleaning of the already scanned data by the subject mater group.\nThe questionnaires were processed at the zones. On completion, computer editing was also carried out to ensure the integrity of the data. .","method_notes":"The data processing analysis involved Six main stages: \nDevelopment of data scanning screen. \nTraining of data processing staff. \nManual editing and coding. \nData entry and scanning into a data base in SPSS. \nComputer editing. \nVerification and conversion.\n\nThe table were then generated using SPSS."},"analysis_info":{"response_rate":"At National basis, 99.3 percent response rate was acheived at EA level .\n\nWhile 82.7 percent was acheived at  housing units level.","sampling_error_estimates":"No sampling error estimate","data_appraisal":"The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were three levels of supervision involving the supervisors at the first level, CBN staff, NBS State Officers and Zonal Controllers at second level and finally the NBS\/NCC Headquarters staff constituting the third level supervision."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"The confidentiality of the individual respondent is protected by law (Statistical Act 2007).\nThis 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.","required":"yes","form_no":"","uri":""}],"contact":[{"name":"National Bureau of Statistics (NBS)","affiliation":"Federal Government of Nigeria (FGN)","email":"feedback@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"}],"cit_req":"National Bureau of Statistics, Nigeria, General  Household Survey (NGA) 2006-v.1.0","conditions":"A comprehensive data access policy is been developed by NBS, however section 27 of the Statistical Act 2007 outlines the data access obligation of data producers which includes the realease of properly anonymized micro data.","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."}}},"schematype":"survey"}